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 621–630 of 1723 papers

Title	Date	Tasks	Status	Score
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization	Nov 26, 2018	2D Object Detection3D Object Detection	CodeCode Available	5
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking	Apr 9, 2025	Autonomous DrivingLanguage Modeling	CodeCode Available	5
Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud	Mar 23, 2019	3D Object DetectionDepth Estimation	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
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations	Dec 1, 2019	Scene Understanding	CodeCode Available	5
Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data	Jan 31, 2024	BenchmarkingChange Detection	CodeCode Available	5
Constructing a Visual Relationship Authenticity Dataset	Oct 11, 2020	Relationship DetectionScene Understanding	CodeCode Available	5
MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and Modalities	Aug 14, 2020	Representation LearningScene Understanding	CodeCode Available	5
MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios	Dec 27, 2024	Autonomous DrivingLanguage Modeling	CodeCode Available	5
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding	Dec 22, 2022	Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATION	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