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 951–1000 of 1723 papers

TitleStatusHype
MUVOD: A Novel Multi-view Video Object Segmentation Dataset and A Benchmark for 3D Segmentation—0
MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views—0
N2F2: Hierarchical Scene Understanding with Nested Neural Feature Fields—0
Natural Language Guided Visual Relationship Detection—0
NavigationNet: A Large-scale Interactive Indoor Navigation Dataset—0
Navigation-Oriented Scene Understanding for Robotic Autonomy: Learning to Segment Driveability in Egocentric Images—0
DGOcc: Depth-aware Global Query-based Network for Monocular 3D Occupancy Prediction—0
Near, far: Patch-ordering enhances vision foundation models' scene understanding—0
Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation—0
Designing DNNs for a trade-off between robustness and processing performance in embedded devices—0
Neural Implicit Dense Semantic SLAM—0
Neural Mesh Refiner for 6-DoF Pose Estimation—0
Neural Part Priors: Learning to Optimize Part-Based Object Completion in RGB-D Scans—0
Neural Projection Mapping Using Reflectance Fields—0
Neural Radiance Field-based Visual Rendering: A Comprehensive Review—0
Zero-Shot Semantic Segmentation via Spatial and Multi-Scale Aware Visual Class Embedding—0
Neural Radiance Fields for the Real World: A Survey—0
Neural Rendering in a Room: Amodal 3D Understanding and Free-Viewpoint Rendering for the Closed Scene Composed of Pre-Captured Objects—0
DEF-oriCORN: efficient 3D scene understanding for robust language-directed manipulation without demonstrations—0
Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera—0
Neural Scene De-Rendering—0
Neuromorphic Visual Scene Understanding with Resonator Networks—0
Designing Deep Networks for Surface Normal Estimation—0
Newtonian Scene Understanding: Unfolding the Dynamics of Objects in Static Images—0
Next-Best-Trajectory Planning of Robot Manipulators for Effective Observation and Exploration—0
Unsupervised Foveal Vision Neural Networks with Top-Down Attention—0
NIS-SLAM: Neural Implicit Semantic RGB-D SLAM for 3D Consistent Scene Understanding—0
Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods—0
Unsupervised Image Segmentation by Mutual Information Maximization and Adversarial Regularization—0
Non-maximum Suppression Also Closes the Variational Approximation Gap of Multi-object Variational Autoencoders—0
Not All Relations are Equal: Mining Informative Labels for Scene Graph Generation—0
Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network—0
Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
Not Using the Car to See the Sidewalk -- Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
Novel 3D Scene Understanding Applications From Recurrence in a Single Image—0
Novel-view Synthesis and Pose Estimation for Hand-Object Interaction from Sparse Views—0
NuGrounding: A Multi-View 3D Visual Grounding Framework in Autonomous Driving—0
Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation—0
Depth Estimation using Weighted-loss and Transfer Learning—0
O2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation—0
DepthCut: Improved Depth Edge Estimation Using Multiple Unreliable Channels—0
Object-agnostic Affordance Categorization via Unsupervised Learning of Graph Embeddings—0
Object as Distribution—0
Why my photos look sideways or upside down? Detecting Canonical Orientation of Images using Convolutional Neural Networks—0
Object-Aware DINO (Oh-A-Dino): Enhancing Self-Supervised Representations for Multi-Object Instance Retrieval—0
Object Aware Egocentric Online Action Detection—0
AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model—0
Object-Centric Scene Representations using Active Inference—0
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization—0
Object-level 3D Semantic Mapping using a Network of Smart Edge Sensors—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