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 751–775 of 1723 papers

TitleStatusHype
Surgical Scene Segmentation by Transformer With Asymmetric Feature EnhancementCode0
PerspectiveNet: Multi-View Perception for Dynamic Scene Understanding—0
Large Language Models for Autonomous Driving (LLM4AD): Concept, Benchmark, Experiments, and Challenges—0
Part-Whole Relational Fusion Towards Multi-Modal Scene UnderstandingCode0
SAM-Guided Masked Token Prediction for 3D Scene Understanding—0
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications—0
Enhancing Single Image to 3D Generation using Gaussian Splatting and Hybrid Diffusion Priors—0
3D Vision-Language Gaussian Splatting—0
A transition towards virtual representations of visual scenes—0
Test-Time Intensity Consistency Adaptation for Shadow Detection—0
Evaluating the Impact of Point Cloud Colorization on Semantic Segmentation Accuracy—0
Open-RGBT: Open-vocabulary RGB-T Zero-shot Semantic Segmentation in Open-world Environments—0
Resource-Efficient Multiview Perception: Integrating Semantic Masking with Masked Autoencoders—0
Diffusion Models in 3D Vision: A Survey—0
In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding—0
Fast Object Detection with a Machine Learning Edge Device—0
SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Models—0
RESSCAL3D++: Joint Acquisition and Semantic Segmentation of 3D Point CloudsCode0
A Critical Assessment of Visual Sound Source Localization Models Including Negative AudioCode0
Class-Agnostic Visio-Temporal Scene Sketch Semantic Segmentation—0
You Only Speak Once to See—0
LLaVA-3D: A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness—0
Scene Understanding in Pick-and-Place Tasks: Analyzing Transformations Between Initial and Final Scenes—0
OW-Rep: Open World Object Detection with Instance Representation Learning—0
Diffusion-based RGB-D Semantic Segmentation with Deformable Attention Transformer—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