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 551–575 of 1723 papers

TitleStatusHype
3D Shape Augmentation with Content-Aware Shape Resizing—0
Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception—0
EgoSplat: Open-Vocabulary Egocentric Scene Understanding with Language Embedded 3D Gaussian Splatting—0
EgoGaussian: Dynamic Scene Understanding from Egocentric Video with 3D Gaussian Splatting—0
Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation—0
AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis—0
Egocentric Image Captioning for Privacy-Preserved Passive Dietary Intake Monitoring—0
Egocentric Activity Recognition and Localization on a 3D Map—0
Efficient Point Transformer for Large-scale 3D Scene Understanding—0
A Preprocessing and Postprocessing Voxel-based Method for LiDAR Semantic Segmentation Improvement in Long Distance—0
3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer—0
Efficient Label Collection for Unlabeled Image Datasets—0
Efficient Interactive 3D Multi-Object Removal—0
CAGS: Open-Vocabulary 3D Scene Understanding with Context-Aware Gaussian Splatting—0
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving—0
CaDIS: Cataract Dataset for Image Segmentation—0
AdaToken-3D: Dynamic Spatial Gating for Efficient 3D Large Multimodal-Models Reasoning—0
360^ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer—0
Efficient 3D Instance Mapping and Localization with Neural Fields—0
Real-time Semantic Segmentation with Context Aggregation Network—0
EarthNets: Empowering AI in Earth Observation—0
EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding—0
BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding—0
Application of Multimodal Large Language Models in Autonomous Driving—0
DEF-oriCORN: efficient 3D scene understanding for robust language-directed manipulation without demonstrations—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