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 481–490 of 1723 papers

Title	Date	Tasks	Status	Score
Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understanding	Apr 20, 2025	Autonomous DrivingImage Captioning	CodeCode Available	5
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models	Apr 6, 2025	Computational EfficiencyGeneral Knowledge	CodeCode Available	5
A Review on Deep Learning Techniques Applied to Semantic Segmentation	Apr 22, 2017	Autonomous DrivingDeep Learning	CodeCode Available	5
ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation	Oct 9, 2017	GPUReal-Time Semantic Segmentation	CodeCode Available	5
PENet: A Joint Panoptic Edge Detection Network	Mar 15, 2023	Edge DetectionMulti-Task Learning	CodeCode Available	5
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video	May 27, 2019	Inductive BiasModel Predictive Control	CodeCode Available	5
Part-Whole Relational Fusion Towards Multi-Modal Scene Understanding	Oct 19, 2024	Autonomous Drivingobject-detection	CodeCode Available	5
CARL-D: A vision benchmark suite and large scale dataset for vehicle detection and scene segmentation	Feb 17, 2022	2D Object DetectionAutonomous Driving	CodeCode Available	5
Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous Racing	Dec 24, 2024	Autonomous DrivingAutonomous Racing	CodeCode Available	5
Parsing Geometry Using Structure-Aware Shape Templates	Aug 3, 2018	ObjectObject Recognition	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