Papers with Code 아카이브

Monocular 3D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 16
보존된 평가 기록: 72

Monocular 3D Object Detection is the task to draw 3D bounding box around objects in a single 2D RGB image. It is localization task but without any extra information like depth or other sensors or multiple-images.

코드

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

https://github.com/AutoAILab/FusionDepth

공식 코드

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

https://github.com/Cc-Hy/CMKD

공식 코드

Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection

https://github.com/KenYu910645/perspective-aware-convolution

공식 코드

Perspective-aware Convolution for Monocular 3D Object Detection

https://github.com/MasterHow/CoBEV

공식 코드

CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity

https://github.com/Owen-Liuyuxuan/visualDet3D

공식 코드

Ground-aware Monocular 3D Object Detection for Autonomous Driving

https://github.com/Rock-100/MonoDet

공식 코드

Geometry-based Distance Decomposition for Monocular 3D Object Detection

https://github.com/TRAILab/CaDDN

공식 코드

Categorical Depth Distribution Network for Monocular 3D Object Detection

https://github.com/Traffic-X/MonoLSS

공식 코드

MonoLSS: Learnable Sample Selection For Monocular 3D Detection

https://github.com/UVA-Computer-Vision-Lab/ovmono3d

공식 코드

Open Vocabulary Monocular 3D Object Detection

https://github.com/WYFDUT/MonoASRH

공식 코드

Efficient Feature Aggregation and Scale-Aware Regression for Monocular 3D Object Detection

https://github.com/Xianpeng919/MonoCon

공식 코드

Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection

https://github.com/YinminZhang/MonoGeo

공식 코드

Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detection

https://github.com/Zengyi-Qin/MonoGRNet

공식 코드

MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization

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/amazon-research/progressive-coordinate-transforms

공식 코드

Progressive Coordinate Transforms for Monocular 3D Object Detection

https://github.com/arcaninez/odm3d

공식 코드

ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object Detection

https://github.com/bravegroup/dcd

공식 코드

Densely Constrained Depth Estimator for Monocular 3D Object Detection

https://github.com/cfzd/monoground

공식 코드

MonoGround: Detecting Monocular 3D Objects from the Ground

https://github.com/chengzhag/Implicit3DUnderstanding

공식 코드

Holistic 3D Scene Understanding from a Single Image with Implicit Representation

https://github.com/cskkxjk/mononerd

공식 코드

MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection

https://github.com/dingmyu/D4LCN

공식 코드

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

https://github.com/drilistbox/3dppe

공식 코드

3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection Transformers

https://github.com/drl-casia/mvm3d

공식 코드

MVM3Det: A Novel Method for Multi-view Monocular 3D Detection

https://github.com/dyxm/pm-hmcw

공식 코드

Monocular 2D Camera-based Proximity Monitoring for Human-Machine Collision Warning on Construction Sites

https://github.com/dyxm/vcvw-3d

공식 코드

VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D Annotations

https://github.com/elvintanhust/monocd

공식 코드

MonoCD: Monocular 3D Object Detection with Complementary Depths

https://github.com/fengziyue/FusionDepth

공식 코드

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

https://github.com/fudan-zvg/DDMP

공식 코드

Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection

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

공식 코드

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

https://github.com/google-research-datasets/Objectron

공식 코드

Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations

https://github.com/gtzly/FADNet

공식 코드

Monocular 3D Object Detection with Sequential Feature Association and Depth Hint Augmentation

https://github.com/gujiaqivadin/HomographyLoss

공식 코드

Homography Loss for Monocular 3D Object Detection

https://github.com/gyhandy/3d-copy-paste

공식 코드

3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection

https://github.com/hoiliu-0801/monotakd

공식 코드

MonoTAKD: Teaching Assistant Knowledge Distillation for Monocular 3D Object Detection

https://github.com/kuanchihhuang/moma-m3t

공식 코드

Delving into Motion-Aware Matching for Monocular 3D Object Tracking

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