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 676–700 of 1723 papers

TitleStatusHype
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural ImagesCode0
From Node to Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot DetectionCode0
Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer DistanceCode0
From Feature Importance to Natural Language Explanations Using LLMs with RAGCode0
CNN-based Lidar Point Cloud De-Noising in Adverse WeatherCode0
Loss Switching Fusion with Similarity Search for Video ClassificationCode0
LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action RecognitionCode0
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual SemanticsCode0
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene UnderstandingCode0
Lightweight integration of 3D features to improve 2D image segmentationCode0
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from VideoCode0
Leveraging Acoustic Images for Effective Self-Supervised Audio Representation LearningCode0
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene UnderstandingCode0
FlowGrad: Using Motion for Visual Sound Source LocalizationCode0
Flow-based GAN for 3D Point Cloud Generation from a Single ImageCode0
Aerial Scene Understanding in The Wild: Multi-Scene Recognition via Prototype-based Memory NetworksCode0
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field EstimationCode0
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph GenerationCode0
ASI-Seg: Audio-Driven Surgical Instrument Segmentation with Surgeon Intention UnderstandingCode0
Matterport3D: Learning from RGB-D Data in Indoor EnvironmentsCode0
Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge FindingsCode0
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry PriorsCode0
Learning Monocular Depth by Distilling Cross-domain Stereo NetworksCode0
Learning Panoptic Segmentation from Instance ContoursCode0
Language-based Colorization of Scene SketchesCode0
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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