https://github.com/xiandaguo/openstereo
공식 코드OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline
Papers with Code 아카이브
Stereo Disparity Estimation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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/xzleo/hinge-wasserstein
공식 코드Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks
https://github.com/y0uchenz/recsm
공식 코드A Flexible Recursive Network for Video Stereo Matching Based on Residual Estimation
https://github.com/yanivw12/gs2mesh
공식 코드GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views
https://github.com/yaochengtang/decnet
공식 코드https://github.com/yihui-he/epipolar-transformers
공식 코드https://github.com/youmi-zym/temporalstereo
공식 코드TemporalStereo: Efficient Spatial-Temporal Stereo Matching Network
https://github.com/yuhuaxu/monostereofusion
공식 코드Depth Estimation by Combining Binocular Stereo and Monocular Structured-Light
https://github.com/zhuofeng-wu/qpdnet
공식 코드https://github.com/zhuxing0/SR-Stereov1-DAPE
공식 코드SR-Stereo & DAPE: Stepwise Regression and Pre-trained Edges for Practical Stereo Matching
https://github.com/ziweiwwang/shef
공식 코드https://github.com/ztsrxh/DVANet
공식 코드Depth-aware Volume Attention for Texture-less Stereo Matching
https://github.com/ztsrxh/roadbev
공식 코드https://github.com/zwxu064/RANP
공식 코드RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs
https://github.com/zyangchen/hart
공식 코드Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer
https://github.com/zyangchen/mocha-stereo
공식 코드MoCha-Stereo: Motif Channel Attention Network for Stereo Matching
https://github.com/zzzkkkyyy/padenet
공식 코드Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor Scenes
https://github.com/3dcvdeveloper/bgnet
https://github.com/AvrilCheng/LidarStereoNet
https://github.com/ChelseaGH/sidewalk_prototype_AI_Hub
https://github.com/FloralZhao/MVPSNet
https://github.com/MindCode-4/code-5/tree/main/yolos
YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection
https://github.com/Mirmix/ddlmvs
https://github.com/UCI-ISA-Lab/MultiHeadDepth-HomoDepth
MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching
https://github.com/andrewlstewart/StereoNet_PyTorch
StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction
https://github.com/apchenstu/mvsnerf
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching
https://github.com/bartn8/vppstereo
https://github.com/brainless-afk/Binary_Stereo_Matching
https://github.com/bruno-31/groupsc
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding
https://github.com/cv-stuttgart/springwebsite
Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo
https://github.com/erezposner/Fast_Dense_Feature_Extraction
https://github.com/gengshan-y/high-res-stereo
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.