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 241–250 of 1723 papers

Title	Date	Tasks	Status	Hype
Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color Contrast	May 31, 2023	3D Instance Segmentation3D Object Detection	CodeCode Available	1
Multi-Scale Attention for Audio Question Answering	May 29, 2023	Audio Question AnsweringQuestion Answering	CodeCode Available	1
Generating Visual Spatial Description via Holistic 3D Scene Understanding	May 19, 2023	Scene UnderstandingText Generation	CodeCode Available	1
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models	May 15, 2023	3D Object DetectionImage Captioning	CodeCode Available	1
Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyond	May 11, 2023	Scene Understanding	CodeCode Available	1
DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization	Apr 30, 2023	DecoderNeRF	CodeCode Available	1
A Review of Panoptic Segmentation for Mobile Mapping Point Clouds	Apr 27, 2023	Instance SegmentationPanoptic Segmentation	CodeCode Available	1
RGB-D Indiscernible Object Counting in Underwater Scenes	Apr 23, 2023	BenchmarkingDepth Estimation	CodeCode Available	1
Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic Segmentation	Apr 22, 2023	Autonomous DrivingKnowledge Distillation	CodeCode Available	1
Advances in Deep Concealed Scene Understanding	Apr 21, 2023	Scene UnderstandingSemantic Segmentation	CodeCode Available	1

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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