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 551600 of 1723 papers

TitleStatusHype
Distance Matters in Human-Object Interaction DetectionCode0
An Information-Theoretic Metric of Transferability for Task Transfer LearningCode0
Parsing Natural Scenes and Natural Language with Recursive Neural NetworksCode0
BlitzNet: A Real-Time Deep Network for Scene UnderstandingCode0
PanoRecon: Real-Time Panoptic 3D Reconstruction from Monocular VideoCode0
Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor ScenesCode0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous RacingCode0
PENet: A Joint Panoptic Edge Detection NetworkCode0
Dilated Residual NetworksCode0
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection InferenceCode0
OVGaussian: Generalizable 3D Gaussian Segmentation with Open VocabulariesCode0
Adapting Deep Network Features to Capture Psychological RepresentationsCode0
OVeNet: Offset Vector Network for Semantic SegmentationCode0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene UnderstandingCode0
Bidirectional Multi-scale Attention Networks for Semantic Segmentation of Oblique UAV ImageryCode0
OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy RepresentationCode0
On the iterative refinement of densely connected representation levels for semantic segmentationCode0
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency DetectionCode0
On the Structures of Representation for the Robustness of Semantic Segmentation to Input CorruptionCode0
One model to use them all: Training a segmentation model with complementary datasetsCode0
Beyond Human Perception: Understanding Multi-Object World from Monocular ViewCode0
An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutionsCode0
DenseASPP for Semantic Segmentation in Street ScenesCode0
Deep Video Deblurring for Hand-Held CamerasCode0
Deep Video DeblurringCode0
Deep Surface Normal Estimation with Hierarchical RGB-D FusionCode0
A Critical Assessment of Visual Sound Source Localization Models Including Negative AudioCode0
Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance FieldsCode0
Object Attribute Matters in Visual Question AnsweringCode0
Object-aware Sound Source Localization via Audio-Visual Scene UnderstandingCode0
Benchmarking Feature Upsampling Methods for Vision Foundation Models using Interactive SegmentationCode0
Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a SupercomputerCode0
Non-central panorama indoor datasetCode0
NextStop: An Improved Tracker For Panoptic LIDAR Segmentation DataCode0
Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship DetectionCode0
Neural Radiance Field CodebooksCode0
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance VotingCode0
Neural RGB->D Sensing: Depth and Uncertainty from a Video CameraCode0
Deep Learning based Switching Filter for Impulsive Noise Removal in Color ImagesCode0
BACS: Background Aware Continual Semantic SegmentationCode0
Deep Learning--Based Scene Simplification for Bionic VisionCode0
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous VehicleCode0
AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene UnderstandingCode0
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label UncertaintyCode0
Multi-task Geometric Estimation of Depth and Surface Normal from Monocular 360° ImagesCode0
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?Code0
AVQACL: A Novel Benchmark for Audio-Visual Question Answering Continual LearningCode0
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth EstimationCode0
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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