paper-with-me

3D Object Detection 벤치마크

3D Object Detection on Rope3D

49개 결과 · ⬇ CSV · JSON

AP@0.7

3.6 21.52 39.44 57.35 75.27 2019-07 2026-09 M3D-RPN+(G) — 16.75 (2019-07-13) M3D-RPN+(G) — 16.75 (2019-07-13) M3D-RPN+(G) — 16.75 (2019-07-13) M3D-RPN+(G) — 16.75 (2019-07-13) M3D-RPN+(G) — 16.75 (2019-07-13) M3D-RPN+(G) — 16.75 (2019-07-13) Kinematic3D+(G) — 17.74 (2020-07-19) Kinematic3D+(G) — 17.74 (2020-07-19) Kinematic3D+(G) — 17.74 (2020-07-19) Kinematic3D+(G) — 17.74 (2020-07-19) Kinematic3D+(G) — 17.74 (2020-07-19) Kinematic3D+(G) — 17.74 (2020-07-19) MonoDLE+(G) — 13.58 (2021-03-30) MonoDLE+(G) — 13.58 (2021-03-30) MonoDLE+(G) — 13.58 (2021-03-30) MonoDLE+(G) — 13.58 (2021-03-30) MonoDLE+(G) — 13.58 (2021-03-30) MonoDLE+(G) — 13.58 (2021-03-30) BEVDepth — 42.56 (2022-06-21) BEVDepth — 42.56 (2022-06-21) BEVDepth — 42.56 (2022-06-21) BEVDepth — 42.56 (2022-06-21) BEVDepth — 42.56 (2022-06-21) BEVDepth — 42.56 (2022-06-21) BEVFormer — 24.64 (2022-11-18) BEVFormer — 24.64 (2022-11-18) BEVFormer — 24.64 (2022-11-18) BEVFormer — 24.64 (2022-11-18) BEVFormer — 24.64 (2022-11-18) BEVFormer — 24.64 (2022-11-18) BEVHeight — 45.73 (2023-03-15) BEVHeight — 45.73 (2023-03-15) BEVHeight — 45.73 (2023-03-15) BEVHeight — 45.73 (2023-03-15) BEVHeight — 45.73 (2023-03-15) BEVHeight — 45.73 (2023-03-15) MonoUNI — 75.27 (2023-09-21) MonoUNI — 75.27 (2023-09-21) MonoUNI — 75.27 (2023-09-21) MonoUNI — 75.27 (2023-09-21) MonoUNI — 75.27 (2023-09-21) MonoUNI — 75.27 (2023-09-21) CoBEV — 52.72 (2023-10-04) CoBEV — 52.72 (2023-10-04) CoBEV — 52.72 (2023-10-04) CoBEV — 52.72 (2023-10-04) CoBEV — 52.72 (2023-10-04) CoBEV — 52.72 (2023-10-04) LeAD-M3D — 3.6 (2025-12-05) M3D-RPN+(G) — 16.75 (2019-07-13) Kinematic3D+(G) — 17.74 (2020-07-19) BEVDepth — 42.56 (2022-06-21) BEVHeight — 45.73 (2023-03-15) MonoUNI — 75.27 (2023-09-21)
RankModel AP@0.7 Extra Training Data PaperCodeYear
1 MonoUNI 75.27 ✓ MonoUNI: A Unified Vehicle and Infrastructure-side Monocular 3D Object Detection Network with Sufficient Depth Clues Traffic-X/MonoUNI 2023
2 CoBEV 52.72 CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity MasterHow/CoBEV 2023
3 BEVHeight 45.73 BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection adlab-autodrive/bevheight 2023
4 BEVDepth 42.56 BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection megvii-basedetection/bevdepth · ZRandomize/MatrixVT 2022
5 BEVFormer 24.64 BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision fundamentalvision/BEVFormer · opengvlab/internimage 2022
6 Kinematic3D+(G) 17.74 Kinematic 3D Object Detection in Monocular Video Nicholasli1995/EgoNet · garrickbrazil/kinematic3d 2020
7 M3D-RPN+(G) 16.75 M3D-RPN: Monocular 3D Region Proposal Network for Object Detection garrickbrazil/M3D-RPN · Nicholasli1995/EgoNet · JuliaChae/M3D-RPN-Waymo · +1 2019
8 MonoDLE+(G) 13.58 Delving into Localization Errors for Monocular 3D Object Detection xinzhuma/monodle 2021
9 MonoUNI 75.27 ✓ MonoUNI: A Unified Vehicle and Infrastructure-side Monocular 3D Object Detection Network with Sufficient Depth Clues Traffic-X/MonoUNI 2023
10 CoBEV 52.72 CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity MasterHow/CoBEV 2023
11 BEVHeight 45.73 BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection adlab-autodrive/bevheight 2023
12 BEVDepth 42.56 BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection megvii-basedetection/bevdepth · ZRandomize/MatrixVT 2022
13 BEVFormer 24.64 BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision fundamentalvision/BEVFormer · opengvlab/internimage 2022
14 Kinematic3D+(G) 17.74 Kinematic 3D Object Detection in Monocular Video Nicholasli1995/EgoNet · garrickbrazil/kinematic3d 2020
15 M3D-RPN+(G) 16.75 M3D-RPN: Monocular 3D Region Proposal Network for Object Detection garrickbrazil/M3D-RPN · Nicholasli1995/EgoNet · JuliaChae/M3D-RPN-Waymo · +1 2019
16 MonoDLE+(G) 13.58 Delving into Localization Errors for Monocular 3D Object Detection xinzhuma/monodle 2021
17 MonoUNI 75.27 ✓ MonoUNI: A Unified Vehicle and Infrastructure-side Monocular 3D Object Detection Network with Sufficient Depth Clues Traffic-X/MonoUNI 2023
18 CoBEV 52.72 CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity MasterHow/CoBEV 2023
19 BEVHeight 45.73 BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection adlab-autodrive/bevheight 2023
20 BEVDepth 42.56 BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection megvii-basedetection/bevdepth · ZRandomize/MatrixVT 2022
1–20 / 49 다음 → 페이지당 10 20 50 100