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 1301–1350 of 1723 papers

TitleStatusHype
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth EstimationCode0
Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation—0
A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images—0
Audiovisual Highlight Detection in Videos—0
Bidirectional Multi-scale Attention Networks for Semantic Segmentation of Oblique UAV ImageryCode0
Optical flow and scene flow estimation: A survey—0
Deep Learning--Based Scene Simplification for Bionic VisionCode0
The Ikshana Hypothesis of Human Scene UnderstandingCode0
Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection—0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images—0
BUTLER: Building Understanding in TextWorld via Language for Embodied Reasoning—0
Non-maximum Suppression Also Closes the Variational Approximation Gap of Multi-object Variational Autoencoders—0
Pseudo Label-Guided Multi Task Learning for Scene Understanding—0
Scene Text Detection for Augmented Reality -- Character Bigram Approach to reduce False Positive Rate—0
P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding—0
Classification of Single-View Object Point Clouds—0
Embodied Visual Active Learning for Semantic Segmentation—0
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos—0
Image-Graph-Image Translation via Auto-Encoding—0
Multi-Model Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation—0
Competitive Simplicity for Multi-Task Learning for Real-Time Foggy Scene Understanding via Domain Adaptation—0
Exploring Deep 3D Spatial Encodings for Large-Scale 3D Scene Understanding—0
Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency—0
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation—0
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments—0
FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
Learning Regional Purity for Instance Segmentation on 3D Point CloudsCode0
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds—0
Highway Driving Dataset for Semantic Video Segmentation—0
Real-time Semantic Segmentation with Context Aggregation Network—0
Axiom Learning and Belief Tracing for Transparent Decision Making in Robotics—0
Unsupervised Foveal Vision Neural Networks with Top-Down Attention—0
Learning Panoptic Segmentation from Instance ContoursCode0
DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM—0
Constructing a Visual Relationship Authenticity DatasetCode0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
Weakly Supervised Learning of Multi-Object 3D Scene Decompositions Using Deep Shape Priors—0
Semi-Supervised Learning for Multi-Task Scene Understanding by Neural Graph ConsensusCode0
Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation—0
Semi-Supervised Learning of Multi-Object 3D Scene Representations—0
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
Towards General Purpose Geometry-Preserving Single-View Depth Estimation—0
Interactive Learning for Semantic Segmentation in Earth ObservationCode0
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation—0
On the Structures of Representation for the Robustness of Semantic Segmentation to Input CorruptionCode0
Deep Learning Techniques for Geospatial Data Analysis—0
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds—0
TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module—0
m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural NetworksCode0
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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