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 91–100 of 1723 papers

Title	Date	Tasks	Status	Hype	Score
OpenESS: Event-based Semantic Scene Understanding with Open Vocabularies	May 8, 2024	Domain AdaptationScene Understanding	CodeCode Available	2	5
OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation	Sep 1, 2023	3D Open-Vocabulary Instance Segmentation3D Open-Vocabulary Object Detection	CodeCode Available	2	5
An Egocentric Vision-Language Model based Portable Real-time Smart Assistant	Mar 6, 2025	Language ModelingLanguage Modelling	CodeCode Available	2	5
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion Models	Nov 25, 2024	DenoisingScene Understanding	CodeCode Available	2	5
EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI	Dec 26, 2023	Scene Understanding	CodeCode Available	2	5
Emma-X: An Embodied Multimodal Action Model with Grounded Chain of Thought and Look-ahead Spatial Reasoning	Dec 16, 2024	HallucinationRobot Manipulation	CodeCode Available	2	5
Panoptic Scene Graph Generation	Jul 22, 2022	BenchmarkingPanoptic Scene Graph Generation	CodeCode Available	2	5
Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers	Dec 13, 2023	3D Question Answering (3D-QA)Attribute	CodeCode Available	2	5
EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene Understanding	Dec 5, 2024	PredictionScene Understanding	CodeCode Available	2	5
GaussianPretrain: A Simple Unified 3D Gaussian Representation for Visual Pre-training in Autonomous Driving	Nov 19, 2024	3D Object DetectionAutonomous Driving	CodeCode Available	2	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