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

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Showing 1251–1300 of 1723 papers

TitleStatusHype
Real-time Semantic Segmentation with Context Aggregation Network—0
BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding—0
RS-RAG: Bridging Remote Sensing Imagery and Comprehensive Knowledge with a Multi-Modal Dataset and Retrieval-Augmented Generation Model—0
BUTLER: Building Understanding in TextWorld via Language for Embodied Reasoning—0
Building an Affordances Map with Interactive Perception—0
Visual Jenga: Discovering Object Dependencies via Counterfactual Inpainting—0
S^3M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
S4C: Self-Supervised Semantic Scene Completion with Neural Fields—0
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments—0
BPDO:Boundary Points Dynamic Optimization for Arbitrary Shape Scene Text Detection—0
Safety Assessment for Autonomous Systems' Perception Capabilities—0
BOX3D: Lightweight Camera-LiDAR Fusion for 3D Object Detection and Localization—0
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data—0
SAM2-LOVE: Segment Anything Model 2 in Language-aided Audio-Visual Scenes—0
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation—0
SAM-Guided Masked Token Prediction for 3D Scene Understanding—0
SAMPLE-HD: Simultaneous Action and Motion Planning Learning Environment—0
Boundary Seeking GANs—0
Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images—0
SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset—0
Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans—0
Bottom-up Instance Segmentation using Deep Higher-Order CRFs—0
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding—0
Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation—0
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