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

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Showing 351–360 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
3DP3: 3D Scene Perception via Probabilistic Programming	Oct 30, 2021	ObjectPose Estimation	CodeCode Available	1	5
Dynamic Graph Message Passing Networks for Visual Recognition	Sep 20, 2022	image-classificationImage Classification	CodeCode Available	1	5
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP	Jan 12, 2023	3D Semantic SegmentationContrastive Learning	CodeCode Available	1	5
Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks	Feb 17, 2023	DeblurringDeep Learning	CodeCode Available	1	5
Comprehensive Visual Question Answering on Point Clouds through Compositional Scene Manipulation	Dec 22, 2021	Common Sense ReasoningQuestion Answering	CodeCode Available	1	5
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding	Nov 9, 2015	Decision MakingDecoder	CodeCode Available	1	5
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation	Mar 28, 2023	Panoptic Scene Graph GenerationScene Graph Generation	CodeCode Available	1	5
Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive Learning	Jun 21, 2022	Contrastive LearningDomain Generalization	CodeCode Available	1	5
Holistic 3D Scene Understanding from a Single Image with Implicit Representation	Mar 11, 2021	3D Object Detection3D Shape Reconstruction	CodeCode Available	1	5
Distilled Semantics for Comprehensive Scene Understanding from Videos	Mar 31, 2020	Depth EstimationKnowledge Distillation	CodeCode Available	1	5

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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