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

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Showing 41–50 of 1723 papers

TitleStatusHype
Attention-based transformer models for image captioning across languages: An in-depth survey and evaluation—0
Trajectory Prediction Meets Large Language Models: A SurveyCode5
PhysGaia: A Physics-Aware Dataset of Multi-Body Interactions for Dynamic Novel View SynthesisCode1
SAM2-LOVE: Segment Anything Model 2 in Language-aided Audio-Visual Scenes—0
Learning Sparsity for Effective and Efficient Music Performance Question Answering—0
Tackling View-Dependent Semantics in 3D Language Gaussian SplattingCode2
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry PriorsCode0
SeG-SR: Integrating Semantic Knowledge into Remote Sensing Image Super-Resolution via Vision-Language ModelCode0
DORAEMON: Decentralized Ontology-aware Reliable Agent with Enhanced Memory Oriented Navigation—0
LiDAR Based Semantic Perception for Forklifts in Outdoor Environments—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