https://github.com/mickeykang16/temporaleventstereo
공식 코드Temporal Event Stereo via Joint Learning with Stereoscopic Flow
Papers with Code 아카이브
Stereo Matching
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Stereo Matching is one of the core technologies in computer vision, which recovers 3D structures of real world from 2D images. It has been widely used in areas such as autonomous driving, augmented reality and robotics navigation. Given a pair of rectified stereo images, the goal of Stereo Matching is to compute the disparity for each pixel in the reference image, where disparity is defined as the horizontal displacement between a pair of corresponding pixels in the left and right images.
Source: Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nasa-jpl/guiss
공식 코드Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling Autonomy
https://github.com/naver/croco
공식 코드CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow
https://github.com/nianticlabs/stereo-from-mono
공식 코드https://github.com/ppliuboy/Flow2Stereo
공식 코드Flow2Stereo: Effective Self-Supervised Learning of Optical Flow and Stereo Matching
https://github.com/princeton-vl/raft-stereo
공식 코드RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching
https://github.com/prs-eth/ResDepth
공식 코드ResDepth: A Deep Residual Prior For 3D Reconstruction From High-resolution Satellite Images
https://github.com/qrzyang/pseudo-stereo
공식 코드Pseudo-Stereo Inputs: A Solution to the Occlusion Challenge in Self-Supervised Stereo Matching
https://github.com/rbrandt1/MaxTreeS
공식 코드MTStereo 2.0: improved accuracy of stereo depth estimation withMax-trees
https://github.com/rebecca0011/uavstereo
공식 코드UAVStereo: A Multiple Resolution Dataset for Stereo Matching in UAV Scenarios
https://github.com/rookiepig/CrossScaleStereo
공식 코드https://github.com/ruirangerfan/road_surface_3d_reconstruction_datasets
공식 코드Road surface 3d reconstruction based on dense subpixel disparity map estimation
https://github.com/seungryong/LAF
공식 코드On the confidence of stereo matching in a deep-learning era: a quantitative evaluation
https://github.com/sheng029/whu-stereo
공식 코드WHU-Stereo: A Challenging Benchmark for Stereo Matching of High-Resolution Satellite Images
https://github.com/sicxu/Deep3dPortrait
공식 코드https://github.com/sjtu-visys/sdg-depth
공식 코드Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth Conversion
https://github.com/sonne-ding/lightendostereo
공식 코드LightEndoStereo: A Real-time Lightweight Stereo Matching Method for Endoscopy Images
https://github.com/spadeliu/graft-psmnet
공식 코드GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented Feature
https://github.com/t-taniai/LocalExpStereo
공식 코드Continuous 3D Label Stereo Matching using Local Expansion Moves
https://github.com/tai-wang/depth-from-motion
공식 코드MV-FCOS3D++: Multi-View Camera-Only 4D Object Detection with Pretrained Monocular Backbones
https://github.com/tangshitao/quadtreeattention
공식 코드https://github.com/timmh/socrates
공식 코드SOCRATES: A Stereo Camera Trap for Monitoring of Biodiversity
https://github.com/torrvision/ELAS_SoC
공식 코드Real-Time Dense Stereo Matching With ELAS on FPGA Accelerated Embedded Devices
https://github.com/tqtqliu/et-mvsnet
공식 코드When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo
https://github.com/ucbdrive/hd3
공식 코드Hierarchical Discrete Distribution Decomposition for Match Density Estimation
https://github.com/vita-epfl/DFI-OmniStereo
공식 코드Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation Model
https://github.com/wangqingyu985/plantstereo
공식 코드PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense Reconstruction
https://github.com/weihaosky/MFuseNet
공식 코드Active Perception with A Monocular Camera for Multiscopic Vision
https://github.com/whu-gpcv/satmvs
공식 코드https://github.com/windsrain/selective-stereo
공식 코드Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matching
https://github.com/xiandaguo/openstereo
공식 코드OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline
https://github.com/xueliancheng/hybridstereonet-main
공식 코드https://github.com/xxxupeng/adl
공식 코드https://github.com/xy-guo/GwcNet
공식 코드https://github.com/xy-guo/LIGA-Stereo
공식 코드LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D Detector
https://github.com/y0uchenz/recsm
공식 코드A Flexible Recursive Network for Video Stereo Matching Based on Residual Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.