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 651–660 of 1723 papers

Title	Date	Tasks	Status	Score
Gated Driver Attention Predictor	Aug 1, 2023	Driver Attention MonitoringPrediction	CodeCode Available	5
Gated2Depth: Real-time Dense Lidar from Gated Images	Feb 13, 2019	Scene Understanding	CodeCode Available	5
m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks	Aug 23, 2020	AnatomyData Augmentation	CodeCode Available	5
Matterport3D: Learning from RGB-D Data in Indoor Environments	Sep 18, 2017	General ClassificationScene Understanding	CodeCode Available	5
Loss Switching Fusion with Similarity Search for Video Classification	Jun 27, 2019	ClassificationClustering	CodeCode Available	5
GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation	Oct 2, 2022	Scene UnderstandingSegmentation	CodeCode Available	5
Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance	Sep 10, 2024	Bilevel OptimizationPoint Cloud Completion	CodeCode Available	5
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics	Apr 16, 2018	NavigateScene Understanding	CodeCode Available	5
Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory	Jul 4, 2021	Question AnsweringScene Understanding	CodeCode Available	5
LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action Recognition	Nov 27, 2024	Action RecognitionGraph Attention	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