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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1325 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
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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