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 826–850 of 1723 papers

TitleStatusHype
GaussianBeV: 3D Gaussian Representation meets Perception Models for BeV Segmentation—0
Open Vocabulary 3D Scene Understanding via Geometry Guided Self-Distillation—0
Training-Free Model Merging for Multi-target Domain Adaptation—0
InfoNorm: Mutual Information Shaping of Normals for Sparse-View ReconstructionCode0
Benchmarking Vision Language Models for Cultural Understanding—0
Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape DataCode0
Dense Multimodal Alignment for Open-Vocabulary 3D Scene Understanding—0
BLOS-BEV: Navigation Map Enhanced Lane Segmentation Network, Beyond Line of Sight—0
Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences—0
Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object SearchCode0
LVLM-empowered Multi-modal Representation Learning for Visual Place Recognition—0
Joint prototype and coefficient prediction for 3D instance segmentation—0
Self-supervised Learning via Cluster Distance Prediction for Operating Room Context Awareness—0
Hybrid Primal Sketch: Combining Analogy, Qualitative Representations, and Computer Vision for Scene Understanding—0
PanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction—0
ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding—0
EgoGaussian: Dynamic Scene Understanding from Egocentric Video with 3D Gaussian Splatting—0
PPTFormer: Pseudo Multi-Perspective Transformer for UAV Segmentation—0
3D-MVP: 3D Multiview Pretraining for Robotic Manipulation—0
GPT-4V Explorations: Mining Autonomous Driving—0
EvSegSNN: Neuromorphic Semantic Segmentation for Event Data—0
Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding—0
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features—0
MapVision: CVPR 2024 Autonomous Grand Challenge Mapless Driving Tech Report—0
Category-level Neural Field for Reconstruction of Partially Observed Objects in Indoor EnvironmentCode0
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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