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 1201–1250 of 1723 papers

TitleStatusHype
SEPT: Standard-Definition Map Enhanced Scene Perception and Topology Reasoning for Autonomous Driving—0
SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction—0
Shallow2Deep: Indoor Scene Modeling by Single Image Understanding—0
Shifted-Windows Transformers for the Detection of Cerebral Aneurysms in Microsurgery—0
SIMS: Simulating Stylized Human-Scene Interactions with Retrieval-Augmented Script Generation—0
Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation—0
Simultaneous Segmentation and Recognition: Towards more accurate Ego Gesture Recognition—0
Single Image 3D Without a Single 3D Image—0
Single Image Depth Estimation: An Overview—0
Single-Input Multi-Output Model Merging: Leveraging Foundation Models for Dense Multi-Task Learning—0
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture—0
SkyScenes: A Synthetic Dataset for Aerial Scene Understanding—0
SLGaussian: Fast Language Gaussian Splatting in Sparse Views—0
Small Drone Field Experiment: Data Collection & Processing—0
Small-Variance Nonparametric Clustering on the Hypersphere—0
Smart Infrastructure: A Research Junction—0
SNeL: A Structured Neuro-Symbolic Language for Entity-Based Multimodal Scene Understanding—0
Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition—0
Software-Defined FPGA Accelerator Design for Mobile Deep Learning Applications—0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images—0
So you think you can track?—0
SparseLGS: Sparse View Language Embedded Gaussian Splatting—0
SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Models—0
SpatialLM: Training Large Language Models for Structured Indoor Modeling—0
Spatial Sampling Network for Fast Scene Understanding—0
Spatiotemporal Event Graphs for Dynamic Scene Understanding—0
Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data—0
SpectralGaussians: Semantic, spectral 3D Gaussian splatting for multi-spectral scene representation, visualization and analysis—0
SpeedMachines: Anytime Structured Prediction—0
Spherical World-Locking for Audio-Visual Localization in Egocentric Videos—0
SplatTalk: 3D VQA with Gaussian Splatting—0
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds—0
sshELF: Single-Shot Hierarchical Extrapolation of Latent Features for 3D Reconstruction from Sparse-Views—0
SSNet: Saliency Prior and State Space Model-based Network for Salient Object Detection in RGB-D Images—0
StandardSim: A Synthetic Dataset For Retail Environments—0
Stochastic Future Prediction in Real World Driving Scenarios—0
Str-L Pose: Integrating Point and Structured Line for Relative Pose Estimation in Dual-Graph—0
Semantic and structural image segmentation for prosthetic vision—0
Structural Concept Learning via Graph Attention for Multi-Level Rearrangement Planning—0
Structured agents for physical construction—0
Structured Generative Models for Scene Understanding—0
Neural Language of Thought Models—0
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos—0
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing—0
SUN RGB-D: A RGB-D Scene Understanding Benchmark Suite—0
SUPER: A Novel Lane Detection System—0
SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians—0
Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review—0
SurgiSAM2: Fine-tuning a foundational model for surgical video anatomy segmentation and detection—0
SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networks—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