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 1611–1620 of 1723 papers

TitleStatusHype
GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction—0
GP-VLS: A general-purpose vision language model for surgery—0
Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving—0
Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection—0
Graph-Grounded LLMs: Leveraging Graphical Function Calling to Minimize LLM Hallucinations—0
Towards Scene Understanding with Detailed 3D Object Representations—0
Feature-Realistic Neural Fusion for Real-Time, Open Set Scene Understanding—0
Grounded Objects and Interactions for Video Captioning—0
Feature-Level Collaboration: Joint Unsupervised Learning of Optical Flow, Stereo Depth and Camera Motion—0
Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstruction—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