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 31–40 of 1723 papers

TitleStatusHype
SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting—0
Robust Visual Localization via Semantic-Guided Multi-Scale Transformer—0
Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods—0
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting—0
SpatialLM: Training Large Language Models for Structured Indoor Modeling—0
STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous DrivingCode1
ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimation—0
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs—0
OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data SynthesisCode1
Tactile MNIST: Benchmarking Active Tactile Perception—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