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 641–650 of 1723 papers

Title	Date	Tasks	Status	Score
Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange	Apr 11, 2024	ObjectScene Understanding	CodeCode Available	5
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond Aberrations	Nov 21, 2022	Domain AdaptationScene Understanding	CodeCode Available	5
MC-PanDA: Mask Confidence for Panoptic Domain Adaptation	Jul 19, 2024	Domain AdaptationPanoptic Segmentation	CodeCode Available	5
General-Purpose Deep Point Cloud Feature Extractor	Mar 12, 2018	3D Object Classification3D Point Cloud Classification	CodeCode Available	5
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models	Mar 28, 2016	Scene Understanding	CodeCode Available	5
Hierarchical Spatial Proximity Reasoning for Vision-and-Language Navigation	Mar 18, 2024	Common Sense ReasoningEfficient Exploration	CodeCode Available	5
Matterport3D: Learning from RGB-D Data in Indoor Environments	Sep 18, 2017	General ClassificationScene Understanding	CodeCode Available	5
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many Synthesis	Jun 28, 2023	Scene Understanding	CodeCode Available	5
METEOR Guided Divergence for Video Captioning	Dec 20, 2022	Hierarchical Reinforcement LearningScene Understanding	CodeCode Available	5
Model-based inexact graph matching on top of CNNs for semantic scene understanding	Jan 18, 2023	Brain SegmentationDeep Learning	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