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 441–450 of 1723 papers

Title	Date	Tasks	Status	Hype
Learning Human-Object Interaction Detection using Interaction Points	Mar 31, 2020	Human-Object Interaction DetectionKeypoint Detection	CodeCode Available	1
LayoutMP3D: Layout Annotation of Matterport3D	Mar 30, 2020	Scene Understanding	CodeCode Available	1
Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds	Mar 29, 2020	3D Semantic SegmentationPoint Cloud Segmentation	CodeCode Available	1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks	Mar 28, 2020	3D Medical Imaging SegmentationAction Recognition	CodeCode Available	1
SaccadeNet: A Fast and Accurate Object Detector	Mar 26, 2020	Objectobject-detection	CodeCode Available	1
Who2com: Collaborative Perception via Learnable Handshake Communication	Mar 21, 2020	Multi-agent Reinforcement LearningReinforcement Learning	CodeCode Available	1
Explainable Object-induced Action Decision for Autonomous Vehicles	Mar 20, 2020	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1
Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways	Mar 18, 2020	3D Semantic SegmentationAutonomous Driving	CodeCode Available	1
Scene Completeness-Aware Lidar Depth Completion for Driving Scenario	Mar 15, 2020	Depth CompletionRGBD Semantic Segmentation	CodeCode Available	1
Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image	Feb 27, 2020	3D Object Detection3D Shape Reconstruction	CodeCode Available	1

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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