Papers with Code 아카이브

3D Object Detection From Monocular Images

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평가표: 3
보존된 평가 기록: 15

This is the task of detecting 3D objects from monocular images (as opposed to LiDAR based counterparts). It is usually associated with autonomous driving based tasks.

<span style="color:grey; opacity: 0.6">( Image credit: Orthographic Feature Transform for Monocular 3D Object Detection )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/abhi1kumar/deviant

공식 코드

DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection

https://github.com/abhi1kumar/groomed_nms

공식 코드

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection

https://github.com/abhi1kumar/seabird

공식 코드

SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects

https://github.com/cangumeli/ROCA

공식 코드

ROCA: Robust CAD Model Retrieval and Alignment from a Single Image

https://github.com/facebookresearch/omni3d

공식 코드

Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild

https://github.com/facebookresearch/votenet

공식 코드

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/garrickbrazil/M3D-RPN

공식 코드

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/kuanchihhuang/monodtr

공식 코드

MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer

https://github.com/supermhp/gupnet

공식 코드

Geometry Uncertainty Projection Network for Monocular 3D Object Detection

https://github.com/xinzhuma/monodle

공식 코드

Delving into Localization Errors for Monocular 3D Object Detection

https://github.com/zrrskywalker/monodetr

공식 코드

MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection

https://github.com/AsahiLiu/PointDetectron

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/Harut0726/votenet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/JuliaChae/M3D-RPN-Waymo

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/LONG-9621/VoteNet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/NUAAXQ/MLCVNet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/Nicholasli1995/EgoNet

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/abhi1kumar/M3D-RPN

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/cheng052/BRNet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/hoangcuongbk80/VoteGrasp

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/ikh-innovation/roboweldar-votenet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/lanlan96/3drm

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/lanlan96/arm3d

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/open-mmlab/mmdetection3d

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/qq456cvb/VoteNet

Deep Hough Voting for 3D Object Detection in Point Clouds

https://github.com/tom-roddick/oft

Orthographic Feature Transform for Monocular 3D Object Detection

https://github.com/zaiweizhang/H3DNet

Deep Hough Voting for 3D Object Detection in Point Clouds

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.