Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 741–750 of 1723 papers

Title	Date	Tasks	Status	Hype
Human-centric Scene Understanding for 3D Large-scale Scenarios	Jul 26, 2023	Action RecognitionScene Understanding	CodeCode Available	1
Enhancing image captioning with depth information using a Transformer-based framework	Jul 24, 2023	Image CaptioningImage Paragraph Captioning	—Unverified	0
Challenges for Monocular 6D Object Pose Estimation in Robotics	Jul 22, 2023	6D Pose Estimation using RGBObject	—Unverified	0
Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery	Jul 22, 2023	Continual LearningScene Understanding	CodeCode Available	0
Improving Online Lane Graph Extraction by Object-Lane Clustering	Jul 20, 2023	3D Object DetectionAutonomous Driving	—Unverified	0
Mining Conditional Part Semantics with Occluded Extrapolation for Human-Object Interaction Detection	Jul 19, 2023	Human-Object Interaction DetectionObject	—Unverified	0
CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation	Jul 19, 2023	Representation LearningScene Understanding	CodeCode Available	1
Towards A Unified Agent with Foundation Models	Jul 18, 2023	Efficient ExplorationReinforcement Learning (RL)	—Unverified	0
Human Action Recognition in Still Images Using ConViT	Jul 18, 2023	Action RecognitionAction Recognition In Still Images	—Unverified	0
A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future	Jul 18, 2023	Knowledge Distillationobject-detection	CodeCode Available	2

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All datasets Semantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K val Semantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.44	—	Unverified
2	Team VGAI (TCS Research)	OMQ	0.37	—	Unverified
3	Demo_semantic_SLAM	OMQ	0.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CPN(ResNet-101)	Mean IoU	46.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.35	—	Unverified