Nerf 3d reconstruction

1780af651b4c689b1d46a0d09d50ccd1c0828fdc6df7562977e28f95a3fcce1f. 127a63fc3c4963c87b56a570bd08fc9f63a9677371949efd3c1d0078a4f1df90. 130b8c63e0e2ad06753cbb22d3c760f5603654e76c835552b9f4990db9cf97e4.Temporal reconstruction We can reconstruct video sequences from TV shows where we replace the background with the NeRF rendering and the people with SMPL meshes. We leverage our recovered 3D context (body pose, shape, location, and identity) and HuMoR for this result. Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. ... The Cupboard sequence below shows improved reconstruction of specular surfaces such as the fridge on the right, ...What the research is: Reconstructing objects in 3D is a seminal computer vision problem with AR/VR applications ranging from telepresence to the generation of 3D models for gaming. With photorealistic, versatile 3D reconstruction, it becomes possible to seamlessly combine real and virtual objects on traditional smartphone and laptop screens, as well as on the AR glasses that will power future ...GRAM is able to generate high-quality images with fine details. Moreover, it allows an explicit control of camera viewpoint and achieves highly consistent results across different views. It even maintains strong visual 3D consistency for very thin structures such as bangs of hair, eyeglass, and whiskers of cat. Jun 30, 2022 · Our approach has achieved superior performance on various scenarios in robotic surgery data such as large elastic deformations and tissue cutting. We hope the emerging NeRF-based 3D reconstruction techniques could inspire new pathways for robotic surgery scene understanding, and empower various down-stream clinical-oriented tasks. Acknowledgements. Jun 30, 2022 · Our approach has achieved superior performance on various scenarios in robotic surgery data such as large elastic deformations and tissue cutting. We hope the emerging NeRF-based 3D reconstruction techniques could inspire new pathways for robotic surgery scene understanding, and empower various down-stream clinical-oriented tasks. Acknowledgements. As a byproduct of our method, we can also reconstruct a rough 3D geometry by learning the pose-conditioned downsampled NeRF from 45x45 (1/16 of full images) resolution images with only 7 sampled points along each ray in training: left (predicted geometry), right (reference image), which enables efficient training and inference.Common Objects in 3D (CO3D) is a dataset designed for learning category-specific 3D reconstruction and new-view synthesis using multi-view images of common object categories. The dataset has been introduced in our ICCV 2021 Paper. Something Went Wrong. We're having trouble playing this video. Learn more.Further to the development of blastFoam | Cityscape, we present a demonstration of real-time 3D cityscape reconstruction leveraging NVIDIA's Instant NeRF.The... Temporal reconstruction We can reconstruct video sequences from TV shows where we replace the background with the NeRF rendering and the people with SMPL meshes. We leverage our recovered 3D context (body pose, shape, location, and identity) and HuMoR for this result. Neural RGB-D Surface Reconstruction. Dejan Azinović, Ricardo Martin-Brualla, Dan B Goldman, Matthias Nießner, Justus Thies. CVPR 2022. [ PDF] [ Project] [ Github] Neural 3D Scene Reconstruction with the Manhattan-world Assumption. Haoyu Guo, Sida Peng, Haotong Lin, Qianqian Wang, Guofeng Zhang, Hujun Bao, Xiaowei Zhou. Neural RGB-D Surface Reconstruction. Dejan Azinović, Ricardo Martin-Brualla, Dan B Goldman, Matthias Nießner, Justus Thies. CVPR 2022. [ PDF] [ Project] [ Github] Neural 3D Scene Reconstruction with the Manhattan-world Assumption. Haoyu Guo, Sida Peng, Haotong Lin, Qianqian Wang, Guofeng Zhang, Hujun Bao, Xiaowei Zhou. 23:07:58 Anatomic Double-Bundle and Single-Bundle ACL Reconstruction After ACL Rupture Did Not Differ for Quality of Life at 2 Years / The Journal of Bone and Joint Surgery Gobbi, 2019.This is probably one of the best papers I've seen for this year, it is shockingly good on how well it performs, even tho it takes forever to render :pNeRF: N...Reconstructing a 3D mesh from a collection of 2D images is a long-standing goal in computer vision and graphics. Neural field-based 3D reconstruction methods (e.g., (Oechsle et al., 2021; Wang et al., 2021; Yariv et al., 2021)) have recently gained traction as they can reconstruct high-fidelity meshes for both objects and scenes, surpassing the quality of traditional reconstruction pipelines ...Aug 28, 2022 · The noise reduction method when combined with the 3D scene gives a high-resolution output which is seamless when transitioning between angle and positions. NeRF in Metaverse. There are various key technologies that are essential for building an immersive experience of Metaverse. This includes AI, IoT, AR, Blockchain and 3D reconstruction. See full list on github.com To render this neural radiance field (NeRF) from a particular viewpoint, we: 1) march camera rays through the scene to generate a sampled set of 3D points, 2) use those points and their corresponding 2D viewing directions as input to the neural network to produce an output set of colors and densities, and 3) use classical volume rendering ...Aug 28, 2022 · The noise reduction method when combined with the 3D scene gives a high-resolution output which is seamless when transitioning between angle and positions. NeRF in Metaverse. There are various key technologies that are essential for building an immersive experience of Metaverse. This includes AI, IoT, AR, Blockchain and 3D reconstruction. Aug 10, 2020 · The Google researchers propose NeRF in the Wild (NeRF-W), a novel approach for 3D scene reconstruction of complex outdoor environments from in-the-wild photo collections. Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. Nov 17, 2021 · The uniqueness of NeRF is proved by the number of doors it opens up in the field of computer graphics and deep learning. These range from medical imaging, 3D scene reconstruction, animation industry, relighting a scene to depth estimation. While all of the Constructed nerfs were already known (due to last week's leak), there's a TON of buffs that we didn't know about, including some that are reverts of past nerfs. In fact, it's one of the biggest balance updates in the history of Hearthstone. It looks like this time the top classes have only received...GRAM is able to generate high-quality images with fine details. Moreover, it allows an explicit control of camera viewpoint and achieves highly consistent results across different views. It even maintains strong visual 3D consistency for very thin structures such as bangs of hair, eyeglass, and whiskers of cat. The Top 16 3d Reconstruction Nerf Open Source Projects Categories > Graphics > 3d Reconstruction Topic > Nerf Instant Ngp ⭐ 8,592 Instant neural graphics primitives: lightning fast NeRF and more most recent commit 5 days ago Nerf_pl ⭐ 1,264 NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning most recent commit 2 months agoAug 28, 2022 · The noise reduction method when combined with the 3D scene gives a high-resolution output which is seamless when transitioning between angle and positions. NeRF in Metaverse. There are various key technologies that are essential for building an immersive experience of Metaverse. This includes AI, IoT, AR, Blockchain and 3D reconstruction. curly hair salon seoul 1. Weekly classified NeRF literature. 2. Non-official implementation of Block-NeRF and Mega-NeRF in Pytorch. 3. Train your large-scale NeRF in the wild ...Temporal reconstruction We can reconstruct video sequences from TV shows where we replace the background with the NeRF rendering and the people with SMPL meshes. We leverage our recovered 3D context (body pose, shape, location, and identity) and HuMoR for this result. An interpretable, data-efficient, and scalable neural scene representation. We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct neural radiance fields for view synthesis. Unlike prior works on neural radiance fields that consider per-scene optimization on densely captured images, we propose a generic deep ...Scene-specific implicit 3D semantic representation is obtained by training on colour images and semantic labels with associated poses. Motivated by the enforcement of multi-view consistency and internal coherence within representation, we find that the training process of Semantic-NeRF itself is a multi-view label fusion and propagation process, i.e., fusion via learning.We present Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and novel view synthesis approach for general non-rigid dynamic scenes. Our approach takes RGB images of a dynamic scene as input (e.g., from a monocular video recording), and creates a high-quality space-time geometry and appearance representation. We show that a single handheld consumer-grade camera is sufficient to ...Oct 14, 2021 · NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild. Recent history has seen a tremendous growth of work exploring implicit representations of geometry and radiance, popularized through Neural Radiance Fields (NeRF). Such works are fundamentally based on a (implicit) volumetric representation of occupancy, allowing ... NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild Jason Y. Zhang, Gengshan Yang, Shubham Tulsiani, Deva Ramanan 10/14/2021 Keywords: Sparse Reconstruction, ... (NeRF). Such works are fundamentally based on a (implicit) volumetric representation of occupancy, allowing them to model diverse scene structure including ...In this work we address the challenging problem of multiview 3D surface reconstruction. We introduce Implicit Differentiable Renderer (IDR): a neural network architecture that simultaneously learns the unknown geometry, camera parameters, and a neural renderer that approximates the light reflected from the surface towards the camera. Заказать на детский праздник Нерф-шоу. Сражение на бластерах Nerf на день Рождения.This is why Phong Shading is the de facto standard in computer graphics for video game rendering since the 3D models in the video game typically cannot have more than a RGBD representation due to computation constraints. For more on shading (Bidirectional Reflectance Distribution Function) and computer graphics, see scratchapixel . Temporal reconstruction We can reconstruct video sequences from TV shows where we replace the background with the NeRF rendering and the people with SMPL meshes. We leverage our recovered 3D context (body pose, shape, location, and identity) and HuMoR for this result. Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. ... The Cupboard sequence below shows improved reconstruction of specular surfaces such as the fridge on the right, ...a comparison between 3d reconstruction using nerf neural networks and mvs algorithms on cultural heritage images June 2021 DOI: 10.5194/isprs-archives-XLIII-B2-2021-565-2021 puzzles and survival ultimate challenge 240 Further to the development of blastFoam | Cityscape, we present a demonstration of real-time 3D cityscape reconstruction leveraging NVIDIA's Instant NeRF.The... GRAM is able to generate high-quality images with fine details. Moreover, it allows an explicit control of camera viewpoint and achieves highly consistent results across different views. It even maintains strong visual 3D consistency for very thin structures such as bangs of hair, eyeglass, and whiskers of cat. Aug 10, 2020 · The Google researchers propose NeRF in the Wild (NeRF-W), a novel approach for 3D scene reconstruction of complex outdoor environments from in-the-wild photo collections. This work presents neural radiance for rendering and temporal (4D) reconstruction of humans in motion (H-NeRF), as captured by a sparse set of cameras or even from a monocular video, and constrain it by a structured implicit human body model, represented using signed distance functions. We present neural radiance fields for rendering and temporal (4D) reconstruction of humans in motion (H ...Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. 23:07:58 Anatomic Double-Bundle and Single-Bundle ACL Reconstruction After ACL Rupture Did Not Differ for Quality of Life at 2 Years / The Journal of Bone and Joint Surgery Gobbi, 2019.Common Objects in 3D (CO3D) is a dataset designed for learning category-specific 3D reconstruction and new-view synthesis using multi-view images of common object categories. The dataset has been introduced in our ICCV 2021 Paper. Something Went Wrong. We're having trouble playing this video. Learn more. sopranos atlantic city restaurant1780af651b4c689b1d46a0d09d50ccd1c0828fdc6df7562977e28f95a3fcce1f. 127a63fc3c4963c87b56a570bd08fc9f63a9677371949efd3c1d0078a4f1df90. 130b8c63e0e2ad06753cbb22d3c760f5603654e76c835552b9f4990db9cf97e4.For more options of this reconstruction script, type python endo_pc_reconstruction.py -h. We also build a visualizer to play point cloud animations. To display reconstructed point clouds, type the command as follows. python vis_pc.py --pc_dir logs/ {expname}/reconstructed_pcds_ {epoch} Type python vis_pc.py -h for more options of the visualizer.Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. GRAM is able to generate high-quality images with fine details. Moreover, it allows an explicit control of camera viewpoint and achieves highly consistent results across different views. It even maintains strong visual 3D consistency for very thin structures such as bangs of hair, eyeglass, and whiskers of cat. Scene encoding through unstructured radiance volumes for efficient sampling via Axis-Aligned Bounding Boxes (AABBs) intersections. Mesh reconstruction with appearance through informed re-sampling based on the inverse normals of the scene geometry via Marching Cubes. Modular implementation which is 1.4x faster and at most twice as much memory ...Jun 30, 2022 · Our approach has achieved superior performance on various scenarios in robotic surgery data such as large elastic deformations and tissue cutting. We hope the emerging NeRF-based 3D reconstruction techniques could inspire new pathways for robotic surgery scene understanding, and empower various down-stream clinical-oriented tasks. Acknowledgements. We propose DS-NeRF (Depth-supervised Neural Radiance Fields), a model for learning neural radiance fields that takes advantage of depth supervised by 3D point clouds. Current NeRF methods require many images with known camera parameters -- typically produced by running structure-from-motion (SFM) to estimate poses and a sparse 3D point cloud.One of the reasons NeRF is able to render with great detail is because it encodes a 3D point and associated view direction on a ray using periodic activation functions, i.e., Fourier Features. This innovation was later generalized to multi-layer networks with periodic activations, aka SIREN(SInusoidal REpresentation Networks).The rise of 3D reconstruction models . Recently, Meta announced the release of Implicitron, an extension of PyTorch3D, which is a 3D computer vision research tool for rendering prototypes of real-life objects. ... In March 2022, the Nvidia research team released Instant NeRF, which can reconstruct a 3D scene from 2D images that are taken at ...During last one year, I did a project and published a paper with Bing Wang supervised by Professor Bo Yang, I worked on 3D-based Recognition in Deep Learning and Artificial Intelligent like reproduced Semantic-NeRF and published Instance-NeRF. I am interested in 3D Space Reconstruction, 3D Space Rendering or Robotics Application is also more ...In this work we address the challenging problem of multiview 3D surface reconstruction. We introduce Implicit Differentiable Renderer (IDR): a neural network architecture that simultaneously learns the unknown geometry, camera parameters, and a neural renderer that approximates the light reflected from the surface towards the camera. Further to the development of blastFoam | Cityscape, we present a demonstration of real-time 3D cityscape reconstruction leveraging NVIDIA's Instant NeRF.The... We propose DS-NeRF (Depth-supervised Neural Radiance Fields), a model for learning neural radiance fields that takes advantage of depth supervised by 3D point clouds. Current NeRF methods require many images with known camera parameters -- typically produced by running structure-from-motion (SFM) to estimate poses and a sparse 3D point cloud.Genova, K : Local Deep Implicit Functions for 3D Shape; Mescheder, L : Occupancy networks: Learning 3D reconstruction in function space; Limited by requirement of ground truth 3D geometry (ex : ShapeNet) Recent : relax this requirement by functions that allow neural implicit shape representations to be optimized through 2D images.For more options of this reconstruction script, type python endo_pc_reconstruction.py -h. We also build a visualizer to play point cloud animations. To display reconstructed point clouds, type the command as follows. python vis_pc.py --pc_dir logs/ {expname}/reconstructed_pcds_ {epoch} Type python vis_pc.py -h for more options of the visualizer. oakland county social services Aug 28, 2022 · The noise reduction method when combined with the 3D scene gives a high-resolution output which is seamless when transitioning between angle and positions. NeRF in Metaverse. There are various key technologies that are essential for building an immersive experience of Metaverse. This includes AI, IoT, AR, Blockchain and 3D reconstruction. The Top 16 3d Reconstruction Nerf Open Source Projects Categories > Graphics > 3d Reconstruction Topic > Nerf Instant Ngp ⭐ 8,592 Instant neural graphics primitives: lightning fast NeRF and more most recent commit 5 days ago Nerf_pl ⭐ 1,264 NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning most recent commit 2 months agoWhile all of the Constructed nerfs were already known (due to last week's leak), there's a TON of buffs that we didn't know about, including some that are reverts of past nerfs. In fact, it's one of the biggest balance updates in the history of Hearthstone. It looks like this time the top classes have only received...In this research, an innovative comparison between 3D reconstructions obtained by means of Artificial Intelligence, in particular NeRF Neural Networks, and by Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) open-source algorithms is proposed. The 3D reconstruction comparison is performed on two test cases, one of cultural interest, one useful only for technical discussion. It is known ... Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. ... The Cupboard sequence below shows improved reconstruction of specular surfaces such as the fridge on the right, ...The remote sensing 3D reconstruction of mountain areas has a wide range of applications in surveying, visualization, and game modeling. Different from indoor objects, outdoor mountain reconstruction faces additional challenges, including illumination changes, diversity of textures, and highly irregular surface geometry. Traditional neural network-based methods that lack discriminative features ...See full list on github.com GRAM is able to generate high-quality images with fine details. Moreover, it allows an explicit control of camera viewpoint and achieves highly consistent results across different views. It even maintains strong visual 3D consistency for very thin structures such as bangs of hair, eyeglass, and whiskers of cat. The Google researchers propose NeRF in the Wild (NeRF-W), a novel approach for 3D scene reconstruction of complex outdoor environments from in-the-wild photo collections.Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. In this research, an innovative comparison between 3D reconstructions obtained by means of Artificial Intelligence, in particular NeRF Neural Networks, and by Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) open-source algorithms is proposed. The 3D reconstruction comparison is performed on two test cases, one of cultural interest, one useful only for technical discussion. It is known ... a comparison between 3d reconstruction using nerf neural networks and mvs algorithms on cultural heritage images June 2021 DOI: 10.5194/isprs-archives-XLIII-B2-2021-565-2021TDSF, Surfel, or NeRF) • Key Steps: • Camera tracking: track camera pose w.r.t. global map • Local map building: reconstruction for local region • Global map integration: fuse local reconstruction to global reconstruction 9 Ref: KinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera3D reconstruction of the general anatomy of the right side view of a small marine slug Pseudunela viatoris. In computer vision and computer graphics, 3D reconstruction is the process of capturing the shape and appearance of real objects. This process can be accomplished either by active or passive methods. [1]Mar 04, 2021 · Scene encoding through unstructured radiance volumes for efficient sampling via Axis-Aligned Bounding Boxes (AABBs) intersections. Mesh reconstruction with appearance through informed re-sampling based on the inverse normals of the scene geometry via Marching Cubes. Modular implementation which is 1.4x faster and at most twice as much memory ... Machine/Deep Learning Intern. May 2022 - Jul 2022. Built GUI application with image/video processing functions using PyQT. Applied SLAM/NeRF (Instant-NGP) for 3D scene reconstruction using images with Open3D/MeshLab. Did image stitching/panorama using LOFTR, DISK, ORB/SIFT, Shi-Tomasi, Deep Stitching. Implemented Super Resolution using SwinIR ...The Motoblitz CS-10 is a Nerf blaster that was released in 2022 under the Elite 2.0 series. It is a two-in-one blaster with a top battery-operated clip system blaster and a bottom air-powered pump-action blaster. Similar to other blasters like the Demolisher 2-In-1, the two halves cannot be separated from each other.Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. This is why Phong Shading is the de facto standard in computer graphics for video game rendering since the 3D models in the video game typically cannot have more than a RGBD representation due to computation constraints. For more on shading (Bidirectional Reflectance Distribution Function) and computer graphics, see scratchapixel . Nov 17, 2021 · The uniqueness of NeRF is proved by the number of doors it opens up in the field of computer graphics and deep learning. These range from medical imaging, 3D scene reconstruction, animation industry, relighting a scene to depth estimation. Jun 30, 2022 · Our approach has achieved superior performance on various scenarios in robotic surgery data such as large elastic deformations and tissue cutting. We hope the emerging NeRF-based 3D reconstruction techniques could inspire new pathways for robotic surgery scene understanding, and empower various down-stream clinical-oriented tasks. Acknowledgements. Most single-view 3D reconstruction methods condition neural 3D representations on input images. The majority employs global image features [29, 6, 28, 25, 8], which, while memory efficient, cannot preserve details that are present in the image and often lead to retrieval-like results. Spatially-aligned local image features have been shown toOne of the researchers from Google based out of London, Ben Mildenhall, in June 2022, released a snippet of their newly developed 3D reconstruction model called RawNeRF. This new tool creates well-lit 3D scenes from 2D images. It has been built on their open-source project called MultiNeRF. Check out the code for MultiNeRF here . THE BELAMY cfa reddithorseweb virginia Include a plan to demonstrate a 3D reconstruction given limited 2D input images for scene exploitation. Document progress in a final report and implement in a proof-of-concept software deliverable. This is a Direct to Phase II topic. PHASE II: Develop, integrate, and demonstrate a prototype capable of 3D reconstruction given sample datasets.3D human reconstruction is an important technology connecting the real world and the virtual world, but most of previous work needs expensive computing resources, making it difficult in real-time scenarios. We propose a lightweight human body reconstruction system based on parametric model, which employs only one RGBD camera as input. To generate a human model end to end, we build a fast and ...Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. Scene encoding through unstructured radiance volumes for efficient sampling via Axis-Aligned Bounding Boxes (AABBs) intersections. Mesh reconstruction with appearance through informed re-sampling based on the inverse normals of the scene geometry via Marching Cubes. Modular implementation which is 1.4x faster and at most twice as much memory ...Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. Jul 09, 2022 · Point-NeRF is an extremely fast rendering model. It is a volumetric neural rendering methods like NeRF, generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. Furthermore, Point-NeRF combines the 3D point clouds, with associated neural features, to model a radiance field. One of the researchers from Google based out of London, Ben Mildenhall, in June 2022, released a snippet of their newly developed 3D reconstruction model called RawNeRF. This new tool creates well-lit 3D scenes from 2D images. It has been built on their open-source project called MultiNeRF. Check out the code for MultiNeRF here . THE BELAMYJun 30, 2022 · Our approach has achieved superior performance on various scenarios in robotic surgery data such as large elastic deformations and tissue cutting. We hope the emerging NeRF-based 3D reconstruction techniques could inspire new pathways for robotic surgery scene understanding, and empower various down-stream clinical-oriented tasks. 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