SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 576–600 of 1723 papers

TitleStatusHype
Audio-visual Event Localization on Portrait Mode Short Videos—0
Attributes-aware Visual Emotion Representation Learning—0
PRIMEDrive-CoT: A Precognitive Chain-of-Thought Framework for Uncertainty-Aware Object Interaction in Driving Scene Scenario—0
RS-RAG: Bridging Remote Sensing Imagery and Comprehensive Knowledge with a Multi-Modal Dataset and Retrieval-Augmented Generation Model—0
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language ModelsCode0
Overlap-Aware Feature Learning for Robust Unsupervised Domain Adaptation for 3D Semantic Segmentation—0
TransforMerger: Transformer-based Voice-Gesture Fusion for Robust Human-Robot Communication—0
CoMatcher: Multi-View Collaborative Feature Matching—0
Ross3D: Reconstructive Visual Instruction Tuning with 3D-Awareness—0
Context-Aware Human Behavior Prediction Using Multimodal Large Language Models: Challenges and Insights—0
Zero-Shot 4D Lidar Panoptic Segmentation—0
PhysPose: Refining 6D Object Poses with Physical Constraints—0
Evaluating Compositional Scene Understanding in Multimodal Generative ModelsCode0
Empowering Large Language Models with 3D Situation Awareness—0
Can DeepSeek Reason Like a Surgeon? An Empirical Evaluation for Vision-Language Understanding in Robotic-Assisted Surgery—0
Open-Vocabulary Semantic Segmentation with Uncertainty Alignment for Robotic Scene Understanding in Indoor Building Environments—0
NuGrounding: A Multi-View 3D Visual Grounding Framework in Autonomous Driving—0
Evaluating Multimodal Language Models as Visual Assistants for Visually Impaired Users—0
Endo-TTAP: Robust Endoscopic Tissue Tracking via Multi-Facet Guided Attention and Hybrid Flow-point Supervision—0
Next-Best-Trajectory Planning of Robot Manipulators for Effective Observation and Exploration—0
A Dataset for Semantic Segmentation in the Presence of Unknowns—0
Visual Jenga: Discovering Object Dependencies via Counterfactual Inpainting—0
DINeMo: Learning Neural Mesh Models with no 3D Annotations—0
OpenLex3D: A New Evaluation Benchmark for Open-Vocabulary 3D Scene Representations—0
Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving—0
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified