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 661–670 of 1723 papers

Title	Date	Tasks	Status	Score
METEOR Guided Divergence for Video Captioning	Dec 20, 2022	Hierarchical Reinforcement LearningScene Understanding	CodeCode Available	5
Lightweight integration of 3D features to improve 2D image segmentation	Dec 16, 2022	Image SegmentationScene Understanding	CodeCode Available	5
FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the Wild	Jan 8, 2024	Language ModellingLarge Language Model	CodeCode Available	5
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images	Jan 26, 2016	DiversityGeneral Classification	CodeCode Available	5
From Node to Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot Detection	Feb 15, 2022	Generalized Zero-Shot Object DetectionScene Understanding	CodeCode Available	5
Leveraging Acoustic Images for Effective Self-Supervised Audio Representation Learning	Aug 1, 2020	Cross-Modal RetrievalRepresentation Learning	CodeCode Available	5
From Feature Importance to Natural Language Explanations Using LLMs with RAG	Jul 30, 2024	counterfactualCounterfactual Reasoning	CodeCode Available	5
CNN-based Lidar Point Cloud De-Noising in Adverse Weather	Dec 9, 2019	Autonomous VehiclesScene Understanding	CodeCode Available	5
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene Understanding	Apr 18, 2025	Deep LearningPoint Cloud Completion	CodeCode Available	5
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding	Apr 4, 2023	Autonomous DrivingDomain Adaptation	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