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 701–710 of 1723 papers

TitleStatusHype
Shape Anchor Guided Holistic Indoor Scene UnderstandingCode0
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic DataCode1
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR SequencesCode1
PanoMixSwap Panorama Mixing via Structural Swapping for Indoor Scene Understanding—0
So you think you can track?—0
AmodalSynthDrive: A Synthetic Amodal Perception Dataset for Autonomous Driving—0
HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D ScansCode1
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning—0
Can you text what is happening? Integrating pre-trained language encoders into trajectory prediction models for autonomous driving—0
PAg-NeRF: Towards fast and efficient end-to-end panoptic 3D representations for agricultural robotics—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