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 1091–1100 of 1723 papers

TitleStatusHype
Context-Dependent Diffusion Network for Visual Relationship Detection—0
Panoptic Segmentation Meets Remote Sensing—0
PanopticSplatting: End-to-End Panoptic Gaussian Splatting—0
Context-Aware Human Behavior Prediction Using Multimodal Large Language Models: Challenges and Insights—0
Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model—0
Content-Aware Preserving Image Generation—0
Configurable 3D Scene Synthesis and 2D Image Rendering with Per-Pixel Ground Truth using Stochastic Grammars—0
Real-time Approximate Bayesian Computation for Scene Understanding—0
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds—0
VideoGameBunny: Towards vision assistants for video games—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