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 601–625 of 1723 papers

TitleStatusHype
Boundary Seeking GANs—0
InLUT3D: Challenging real indoor dataset for point cloud analysis—0
DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving—0
DreamAnywhere: Object-Centric Panoramic 3D Scene Generation—0
Bottom-up Instance Segmentation using Deep Higher-Order CRFs—0
3D Scene Understanding at Urban Intersection using Stereo Vision and Digital Map—0
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization—0
DORSal: Diffusion for Object-centric Representations of Scenes et al—0
DORAEMON: Decentralized Ontology-aware Reliable Agent with Enhanced Memory Oriented Navigation—0
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding—0
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs—0
Does CLIP perceive art the same way we do?—0
Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation—0
Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions—0
Do Deep Neural Networks Model Nonlinear Compositionality in the Neural Representation of Human-Object Interactions?—0
Answerability Fields: Answerable Location Estimation via Diffusion Models—0
Indoor Semantic Scene Understanding using Multi-modality Fusion—0
Inferring Shared Attention in Social Scene Videos—0
In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding—0
Interactive Occlusion Boundary Estimation through Exploitation of Synthetic Data—0
DIV-FF: Dynamic Image-Video Feature Fields For Environment Understanding in Egocentric Videos—0
Boosting Cross-spectral Unsupervised Domain Adaptation for Thermal Semantic Segmentation—0
Distraction-Aware Shadow Detection—0
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features—0
An Intelligent Safety System for Human-Centered Semi-Autonomous Vehicles—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