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 511–520 of 1723 papers

TitleStatusHype
Advancing Complex Wide-Area Scene Understanding with Hierarchical Coresets Selection—0
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation—0
Car Segmentation and Pose Estimation using 3D Object Models—0
Enhancing Single Image to 3D Generation using Gaussian Splatting and Hybrid Diffusion Priors—0
A Review and A Robust Framework of Data-Efficient 3D Scene Parsing with Traditional/Learned 3D Descriptors—0
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators—0
Enhancing image captioning with depth information using a Transformer-based framework—0
Enhancing Human-Centered Dynamic Scene Understanding via Multiple LLMs Collaborated Reasoning—0
Can you text what is happening? Integrating pre-trained language encoders into trajectory prediction models for autonomous driving—0
Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding—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