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 721–730 of 1723 papers

Title	Date	Tasks	Status	Score
Label-Attention Transformer with Geometrically Coherent Objects for Image Captioning	Sep 16, 2021	DecoderImage Captioning	CodeCode Available	5
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields	Apr 1, 2019	3D Instance Segmentation3D Semantic Instance Segmentation	CodeCode Available	5
Extremely Fine-Grained Visual Classification over Resembling Glyphs in the Wild	Aug 25, 2024	Contrastive LearningFine-Grained Image Classification	CodeCode Available	5
Adversarial Attacks on Monocular Pose Estimation	Jul 14, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	5
Joint stereo 3D object detection and implicit surface reconstruction	Nov 25, 2021	3D Object DetectionHallucination	CodeCode Available	5
Knowledge-Guided Object Discovery with Acquired Deep Impressions	Mar 19, 2021	ObjectObject Discovery	CodeCode Available	5
Exploring Scene Affinity for Semi-Supervised LiDAR Semantic Segmentation	Aug 21, 2024	3D Semantic SegmentationData Augmentation	CodeCode Available	5
MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and Modalities	Aug 14, 2020	Representation LearningScene Understanding	CodeCode Available	5
Semantic Foreground Inpainting from Weak Supervision	Sep 10, 2019	Scene UnderstandingSemantic Segmentation	CodeCode Available	5
Zoom in on the Plant: Fine-grained Analysis of Leaf, Stem and Vein Instances	Dec 14, 2023	Scene Understanding	CodeCode Available	5

Show:10 25 50

← PrevPage 73 of 173Next →

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