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 901–925 of 1723 papers

TitleStatusHype
Zero-Shot Scene Understanding for Automatic Target Recognition Using Large Vision-Language Models—0
Do Deep Neural Networks Model Nonlinear Compositionality in the Neural Representation of Human-Object Interactions?—0
DIV-FF: Dynamic Image-Video Feature Fields For Environment Understanding in Egocentric Videos—0
Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation—0
MOSE: Monocular Semantic Reconstruction Using NeRF-Lifted Noisy Priors—0
Movies2Scenes: Using Movie Metadata to Learn Scene Representation—0
Moving Beyond Navigation with Active Neural SLAM—0
Moving Object Proposals with Deep Learned Optical Flow for Video Object Segmentation—0
CorNav: Autonomous Agent with Self-Corrected Planning for Zero-Shot Vision-and-Language Navigation—0
UniPLV: Towards Label-Efficient Open-World 3D Scene Understanding by Regional Visual Language Supervision—0
Distraction-Aware Shadow Detection—0
MTANet: Multitask-Aware Network With Hierarchical Multimodal Fusion for RGB-T Urban Scene Understanding—0
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features—0
Distillation of Human-Object Interaction Contexts for Action Recognition—0
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization—0
Disaster Anomaly Detector via Deeper FCDDs for Explainable Initial Responses—0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation—0
Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes—0
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation—0
Multimodal 3D Object Detection on Unseen Domains—0
Multimodal 3D Reasoning Segmentation with Complex Scenes—0
Multi-Modal Attention-based Fusion Model for Semantic Segmentation of RGB-Depth Images—0
Direction-Aware Semi-Dense SLAM—0
DINeMo: Learning Neural Mesh Models with no 3D Annotations—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