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 701–725 of 1723 papers

TitleStatusHype
ObjVariantEnsemble: Advancing Point Cloud LLM Evaluation in Challenging Scenes with Subtly Distinguished Objects—0
Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset—0
GAGS: Granularity-Aware Feature Distillation for Language Gaussian Splatting—0
An Enhanced Classification Method Based on Adaptive Multi-Scale Fusion for Long-tailed Multispectral Point Clouds—0
SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians—0
MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents—0
SLGaussian: Fast Language Gaussian Splatting in Sparse Views—0
TGOSPA Metric Parameters Selection and Evaluation for Visual Multi-object Tracking—0
Event fields: Capturing light fields at high speed, resolution, and dynamic range—0
Visual Lexicon: Rich Image Features in Language Space—0
TB-HSU: Hierarchical 3D Scene Understanding with Contextual Affordances—0
Designing DNNs for a trade-off between robustness and processing performance in embedded devices—0
Assessing the performance of CT image denoisers using Laguerre-Gauss Channelized Hotelling Observer for lesion detection—0
SparseLGS: Sparse View Language Embedded Gaussian Splatting—0
BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding—0
Occam's LGS: A Simple Approach for Language Gaussian Splatting—0
Holistic Understanding of 3D Scenes as Universal Scene Description—0
A Semantic Communication System for Real-time 3D Reconstruction Tasks—0
ChatSplat: 3D Conversational Gaussian Splatting—0
Video-3D LLM: Learning Position-Aware Video Representation for 3D Scene UnderstandingCode0
SIMS: Simulating Stylized Human-Scene Interactions with Retrieval-Augmented Script Generation—0
Quantifying the synthetic and real domain gap in aerial scene understanding—0
InstanceGaussian: Appearance-Semantic Joint Gaussian Representation for 3D Instance-Level Perception—0
On-chip Hyperspectral Image Segmentation with Fully Convolutional Networks for Scene Understanding in Autonomous Driving—0
SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments—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