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 651–675 of 1723 papers

TitleStatusHype
Diffusion Models in 3D Vision: A Survey—0
Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds—0
Diffusion-based RGB-D Semantic Segmentation with Deformable Attention Transformer—0
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice—0
DiffSDFSim: Differentiable Rigid-Body Dynamics With Implicit Shapes—0
Dietary Assessment with Multimodal ChatGPT: A Systematic Analysis—0
Bilateral Adaptation for Human-Object Interaction Detection with Occlusion-Robustness—0
Diagnostics in Semantic Segmentation—0
DGOcc: Depth-aware Global Query-based Network for Monocular 3D Occupancy Prediction—0
An Enhanced Object Detection Model for Scene Graph Generation—0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
Designing DNNs for a trade-off between robustness and processing performance in embedded devices—0
Designing Deep Networks for Surface Normal Estimation—0
An Enhanced Classification Method Based on Adaptive Multi-Scale Fusion for Long-tailed Multispectral Point Clouds—0
Language-Assisted 3D Scene Understanding—0
Learning from Maps: Visual Common Sense for Autonomous Driving—0
Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods—0
Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network—0
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields—0
Depth Estimation using Weighted-loss and Transfer Learning—0
Beyond Recognition: Evaluating Visual Perspective Taking in Vision Language Models—0
Real-time Approximate Bayesian Computation for Scene Understanding—0
DepthCut: Improved Depth Edge Estimation Using Multiple Unreliable Channels—0
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization—0
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds—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