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 1601–1625 of 1723 papers

TitleStatusHype
Matterport3D: Learning from RGB-D Data in Indoor EnvironmentsCode0
From Node to Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot DetectionCode0
CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate RepresentationCode0
Structured Label Inference for Visual UnderstandingCode0
AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene UnderstandingCode0
From Feature Importance to Natural Language Explanations Using LLMs with RAGCode0
m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural NetworksCode0
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose EstimationCode0
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR ScansCode0
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene UnderstandingCode0
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual SemanticsCode0
Loss Switching Fusion with Similarity Search for Video ClassificationCode0
Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer DistanceCode0
AVQACL: A Novel Benchmark for Audio-Visual Question Answering Continual LearningCode0
Continual Learning of Unsupervised Monocular Depth from VideosCode0
FlowGrad: Using Motion for Visual Sound Source LocalizationCode0
An Information-Theoretic Metric of Transferability for Task Transfer LearningCode0
SceneAware: Scene-Constrained Pedestrian Trajectory Prediction with LLM-Guided WalkabilityCode0
LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action RecognitionCode0
Lightweight integration of 3D features to improve 2D image segmentationCode0
Surgical Scene Segmentation by Transformer With Asymmetric Feature EnhancementCode0
Constructing a Visual Relationship Authenticity DatasetCode0
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene UnderstandingCode0
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond AberrationsCode0
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene UnderstandingCode0
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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