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홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

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3D Object Detection From Monocular Images On 7

평가 지표

AP25

AP50

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	AP25	AP50	Paper Title	Repository
MonoDETR	27.13	0.79	MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection	-
MonoDLE	28.99	0.85	Delving into Localization Errors for Monocular 3D Object Detection	-
VoteNet	30.61	3.40	Deep Hough Voting for 3D Object Detection in Point Clouds	-
SeaBird + Image2Maps	35.04	3.14	SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects	-
MonoDTR	39.76	3.02	MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer	-
SeaBird + PanopticBEV	37.12	4.64	SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects	-
Cube R-CNN	15.57	0.80	Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild	-
GrooMeD-NMS	16.12	0.17	GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection	-
BoxNet	23.59	4.08	Deep Hough Voting for 3D Object Detection in Point Clouds	-
GUPNet	27.25	0.87	Geometry Uncertainty Projection Network for Monocular 3D Object Detection	-
DEVIANT	26.96	0.88	DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection	-

0 of 11 row(s) selected.

3D Object Detection From Monocular Images On 7 | SOTA | HyperAI초신경