https://github.com/michael-fonder/M4Depth
공식 코드M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments
Papers with Code 아카이브
Depth Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 14
- 보존된 평가 기록
- 58
Depth Estimation is the task of measuring the distance of each pixel relative to the camera. Depth is extracted from either monocular (single) or stereo (multiple views of a scene) images. Traditional methods use multi-view geometry to find the relationship between the images. Newer methods can directly estimate depth by minimizing the regression loss, or by learning to generate a novel view from a sequence. The most popular benchmarks are KITTI and NYUv2. Models are typically evaluated according to a RMS metric.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/michael-fonder/m4depthu
공식 코드A technique to jointly estimate depth and depth uncertainty for unmanned aerial vehicles
https://github.com/michaelwanggo/endolrmgs
공식 코드https://github.com/microsoft/S2R-DepthNet
공식 코드S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation
https://github.com/mileyan/AnyNet
공식 코드https://github.com/mileyan/Pseudo_Lidar_V2
공식 코드Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
https://github.com/mileyan/pseudo-LiDAR_e2e
공식 코드https://github.com/mileyan/pseudo_lidar
공식 코드https://github.com/minghanz/DepthC3D
공식 코드https://github.com/minghanz/c3d
공식 코드https://github.com/miraiaroha/ACAN
공식 코드Attention-based Context Aggregation Network for Monocular Depth Estimation
https://github.com/mizhenxing/gbi-net
공식 코드Generalized Binary Search Network for Highly-Efficient Multi-View Stereo
https://github.com/mks0601/3DMPPE_POSENET_RELEASE
공식 코드Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
https://github.com/mks0601/3DMPPE_ROOTNET_RELEASE
공식 코드Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
https://github.com/mli0603/stereo-transformer
공식 코드Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers
https://github.com/mmocking/radarcam-depth
공식 코드RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric Scale
https://github.com/mmocking/riders
공식 코드https://github.com/mobarakol/dares
공식 코드https://github.com/mohammedsalah98/pt_fusion
공식 코드https://github.com/mrezaei92/TriHorn-Net
공식 코드TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose Estimation
https://github.com/mrharicot/monodepth
공식 코드Unsupervised Monocular Depth Estimation with Left-Right Consistency
https://github.com/mrobotit/sm4depth
공식 코드SM4Depth: Seamless Monocular Metric Depth Estimation across Multiple Cameras and Scenes by One Model
https://github.com/mrsempress/nerf-detplusplus
공식 코드https://github.com/msscao/acdepth
공식 코드Always Clear Depth: Robust Monocular Depth Estimation under Adverse Weather
https://github.com/mtngld/lsim
공식 코드Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation
https://github.com/mumianyuxin/M3DSSD
공식 코드https://github.com/murinj/big-moe
공식 코드BIG-MoE: Bypass Isolated Gating MoE for Generalized Multimodal Face Anti-Spoofing
https://github.com/murphytju/difffas
공식 코드https://github.com/mvme-hbut/mprlnet
공식 코드https://github.com/nadezola/intothefog_mot17
공식 코드Into the Fog: Evaluating Robustness of Multiple Object Tracking
https://github.com/naiyugao/panopticdepth
공식 코드PanopticDepth: A Unified Framework for Depth-aware Panoptic Segmentation
https://github.com/nana01219/geodsr
공식 코드Learning Continuous Depth Representation via Geometric Spatial Aggregator
https://github.com/nasa-jpl/guiss
공식 코드Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling Autonomy
https://github.com/naufalso/adversarial-manhole
공식 코드https://github.com/naver/croco
공식 코드CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion
https://github.com/naver/dust3r
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.