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

Showing 171180 of 1723 papers

TitleStatusHype
MTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based DecodersCode1
Uni-DVPS: Unified Model for Depth-Aware Video Panoptic SegmentationCode1
CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving ScenesCode1
A Two-Stage Masked Autoencoder Based Network for Indoor Depth CompletionCode1
MuirBench: A Comprehensive Benchmark for Robust Multi-image UnderstandingCode1
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World EnvironmentsCode1
Beyond Appearances: Material Segmentation with Embedded Spectral Information from RGB-D imageryCode1
DTCLMapper: Dual Temporal Consistent Learning for Vectorized HD Map ConstructionCode1
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for ControlCode1
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44Unverified
2Team VGAI (TCS Research)OMQ0.37Unverified
3Demo_semantic_SLAMOMQ0.11Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35Unverified