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 1531–1540 of 1723 papers

Title	Date	Tasks	Status
IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments	Nov 26, 2018	Autonomous NavigationDomain Adaptation	CodeCode Available
Benchmarking Feature Upsampling Methods for Vision Foundation Models using Interactive Segmentation	May 4, 2025	BenchmarkingFeature Upsampling	CodeCode Available
Soft-PHOC Descriptor for End-to-End Word Spotting in Egocentric Scene Images	Sep 4, 2018	AttributeDynamic Time Warping	CodeCode Available
A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain Gap	Jul 31, 2024	Human-Object Interaction DetectionImage Reconstruction	CodeCode Available
Deep Surface Normal Estimation with Hierarchical RGB-D Fusion	Apr 6, 2019	Scene UnderstandingSurface Normal Estimation	CodeCode Available
Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a Supercomputer	Apr 3, 2019	Deep Reinforcement LearningReinforcement Learning	CodeCode Available
Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship Detection	Feb 15, 2019	Relationship DetectionScene Understanding	CodeCode Available
Preferences Prediction using a Gallery of Mobile Device based on Scene Recognition and Object Detection	Jul 10, 2019	Face Recognitionobject-detection	CodeCode Available
Spatial As Deep: Spatial CNN for Traffic Scene Understanding	Dec 17, 2017	Lane DetectionScene Understanding	CodeCode Available
ICGNet: A Unified Approach for Instance-Centric Grasping	Jan 18, 2024	ObjectObject Reconstruction	CodeCode Available

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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