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 1126–1150 of 1723 papers

TitleStatusHype
Learning-based Relational Object Matching Across Views—0
Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation—0
Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes—0
Learning Depth from Single Images with Deep Neural Network Embedding Focal Length—0
Learning Direct Optimization for Scene Understanding—0
Learning from Maps: Visual Common Sense for Autonomous Driving—0
Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation—0
Learning Geometric-Aware Properties in 2D Representation Using Lightweight CAD Models, or Zero Real 3D Pairs—0
Learning in Audio-visual Context: A Review, Analysis, and New Perspective—0
SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes—0
SceneGPT: A Language Model for 3D Scene Understanding—0
Scene Graph Generation: A Comprehensive Survey—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
SceneNet RGB-D: Can 5M Synthetic Images Beat Generic ImageNet Pre-Training on Indoor Segmentation?—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
Scene Summarization: Clustering Scene Videos into Spatially Diverse Frames—0
SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments—0
Scene Text Detection for Augmented Reality -- Character Bigram Approach to reduce False Positive Rate—0
SceneTrilogy: On Human Scene-Sketch and its Complementarity with Photo and Text—0
Scene Understanding Enabled Semantic Communication with Open Channel Coding—0
Scene Understanding for Autonomous Manipulation with Deep Learning—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