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 1021–1030 of 1723 papers

Title	Date	Tasks	Status	Hype
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers	Mar 9, 2022	3D Object DetectionAutonomous Vehicles	CodeCode Available	2
On Steering Multi-Annotations per Sample for Multi-Task Learning	Mar 6, 2022	Instance SegmentationMulti-Task Learning	—Unverified	0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks	Mar 3, 2022	Depth EstimationImage Super-Resolution	—Unverified	0
Hybrid Optimized Deep Convolution Neural Network based Learning Model for Object Detection	Mar 2, 2022	Content-Based Image RetrievalDeep Learning	—Unverified	0
Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation	Mar 2, 2022	Domain AdaptationScene Understanding	CodeCode Available	1
TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation	Feb 27, 2022	Autonomous DrivingKnowledge Distillation	CodeCode Available	1
RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep Learning	Feb 26, 2022	3D Point Cloud ClassificationPoint Cloud Segmentation	CodeCode Available	1
RescueNet: A High Resolution UAV Semantic Segmentation Benchmark Dataset for Natural Disaster Damage Assessment	Feb 24, 2022	Scene UnderstandingSegmentation	CodeCode Available	1
GroupViT: Semantic Segmentation Emerges from Text Supervision	Feb 22, 2022	Object DetectionScene Understanding	CodeCode Available	2
ReorientBot: Learning Object Reorientation for Specific-Posed Placement	Feb 22, 2022	Motion GenerationMotion Planning	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