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

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Showing 501–525 of 1723 papers

TitleStatusHype
Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor ScenesCode0
Parsing Geometry Using Structure-Aware Shape TemplatesCode0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
OVeNet: Offset Vector Network for Semantic SegmentationCode0
OVGaussian: Generalizable 3D Gaussian Segmentation with Open VocabulariesCode0
Instance-Warp: Saliency Guided Image Warping for Unsupervised Domain AdaptationCode0
Efficient ConvNet for Real-time Semantic SegmentationCode0
Efficient Computation Sharing for Multi-Task Visual Scene UnderstandingCode0
OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene UnderstandingCode0
OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy RepresentationCode0
3D Semantic Segmentation of Modular Furniture using rjMCMCCode0
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language ModelsCode0
On the iterative refinement of densely connected representation levels for semantic segmentationCode0
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR SequencesCode0
On the Structures of Representation for the Robustness of Semantic Segmentation to Input CorruptionCode0
Bridging Stereo Matching and Optical Flow via Spatiotemporal CorrespondenceCode0
AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted SurgeryCode0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance FieldsCode0
Dual-Glance Model for Deciphering Social RelationshipsCode0
A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain GapCode0
Box for Mask and Mask for Box: weak losses for multi-task partially supervised learningCode0
APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point CloudsCode0
One model to use them all: Training a segmentation model with complementary datasetsCode0
DRRNet: Macro-Micro Feature Fusion and Dual Reverse Refinement for Camouflaged Object DetectionCode0
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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