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 1276–1300 of 1723 papers

TitleStatusHype
Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning—0
Scenarios: A New Representation for Complex Scene Understanding—0
Scene-aware Human Pose Generation using Transformer—0
Scene-Aware Prompt for Multi-modal Dialogue Understanding and Generation—0
Visual Lexicon: Rich Image Features in Language Space—0
Boosting Cross-spectral Unsupervised Domain Adaptation for Thermal Semantic Segmentation—0
BLOS-BEV: Navigation Map Enhanced Lane Segmentation Network, Beyond Line of Sight—0
SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis—0
Counterfactual Critic Multi-Agent Training for Scene Graph Generation—0
SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes—0
SceneGPT: A Language Model for 3D Scene Understanding—0
BlindSpotNet: Seeing Where We Cannot See—0
Scene Graph Generation: A Comprehensive Survey—0
ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding—0
A Comprehensive Survey of Scene Graphs: Generation and Application—0
Scene Image is Non-Mutually Exclusive - A Fuzzy Qualitative Scene Understanding—0
Scene-Independent Group Profiling in Crowd—0
Scene Map-based Prompt Tuning for Navigation Instruction Generation—0
3D Question Answering for City Scene Understanding—0
SceneNet RGB-D: Can 5M Synthetic Images Beat Generic ImageNet Pre-Training on Indoor Segmentation?—0
3D Pose Regression using Convolutional Neural Networks—0
Scene-R1: Video-Grounded Large Language Models for 3D Scene Reasoning without 3D Annotations—0
Scene recognition based on DNN and game theory with its applications in human-robot interaction—0
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting—0
Blending Learning and Inference in Structured Prediction—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