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 501–510 of 1723 papers

TitleStatusHype
SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis—0
SemanticSplat: Feed-Forward 3D Scene Understanding with Language-Aware Gaussian Fields—0
PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly—0
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting—0
Robust Visual Localization via Semantic-Guided Multi-Scale Transformer—0
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting—0
Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods—0
SpatialLM: Training Large Language Models for Structured Indoor Modeling—0
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs—0
ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimation—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