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 501–510 of 1723 papers

Title	Date	Tasks	Status	Score
OVGaussian: Generalizable 3D Gaussian Segmentation with Open Vocabularies	Dec 31, 2024	3DGS3D Semantic Segmentation	CodeCode Available	5
OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding	Jul 10, 2025	Scene UnderstandingSpatial Reasoning	CodeCode Available	5
Parsing Geometry Using Structure-Aware Shape Templates	Aug 3, 2018	ObjectObject Recognition	CodeCode Available	5
OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy Representation	Mar 18, 2024	3D Reconstruction3D Scene Reconstruction	CodeCode Available	5
Instance-Warp: Saliency Guided Image Warping for Unsupervised Domain Adaptation	Mar 19, 2024	Domain AdaptationObject	CodeCode Available	5
On the iterative refinement of densely connected representation levels for semantic segmentation	Apr 30, 2018	Image SegmentationScene Understanding	CodeCode Available	5
Efficient ConvNet for Real-time Semantic Segmentation	Jun 1, 2017	GPUReal-Time Semantic Segmentation	CodeCode Available	5
Efficient Computation Sharing for Multi-Task Visual Scene Understanding	Mar 16, 2023	Multi-Task LearningScene Understanding	CodeCode Available	5
On the Structures of Representation for the Robustness of Semantic Segmentation to Input Corruption	Sep 2, 2020	Scene UnderstandingSegmentation	CodeCode Available	5
One model to use them all: Training a segmentation model with complementary datasets	Feb 29, 2024	AllAnatomy	CodeCode Available	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