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 751–775 of 1723 papers

TitleStatusHype
Open Scene Understanding: Grounded Situation Recognition Meets Segment Anything for Helping People with Visual ImpairmentsCode1
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous VehicleCode0
Smart Infrastructure: A Research Junction—0
The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context DatasetCode1
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic SurgeryCode1
Test-Time Adaptation for Nighttime Color-Thermal Semantic Segmentation—0
PSDR-Room: Single Photo to Scene using Differentiable Rendering—0
Towards accurate instance segmentation in large-scale LiDAR point cloudsCode1
Object Recognition System on a Tactile Device for Visually Impaired—0
AVSegFormer: Audio-Visual Segmentation with TransformerCode1
Artifacts Mapping: Multi-Modal Semantic Mapping for Object Detection and 3D Localization—0
Towards Open Vocabulary Learning: A SurveyCode2
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many SynthesisCode0
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos—0
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties—0
SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV FusionCode1
OpenMask3D: Open-Vocabulary 3D Instance SegmentationCode2
Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation—0
Semantic-aware Transmission for Robust Point Cloud Classification—0
Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape PriorCode1
CorNav: Autonomous Agent with Self-Corrected Planning for Zero-Shot Vision-and-Language Navigation—0
PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic SegmentationCode1
Estimating Generic 3D Room Structures from 2D AnnotationsCode1
DORSal: Diffusion for Object-centric Representations of Scenes et al—0
Neural Projection Mapping Using Reflectance Fields—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