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 926–950 of 1723 papers

TitleStatusHype
Moving Object Proposals with Deep Learned Optical Flow for Video Object Segmentation—0
InCoRo: In-Context Learning for Robotics Control with Feedback Loops—0
Neural Language of Thought Models—0
Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation dataCode0
Non-central panorama indoor datasetCode0
Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems—0
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents—0
S^3M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving—0
ICGNet: A Unified Approach for Instance-Centric GraspingCode0
BPDO:Boundary Points Dynamic Optimization for Arbitrary Shape Scene Text Detection—0
SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding—0
Class-Imbalanced Semi-Supervised Learning for Large-Scale Point Cloud Semantic Segmentation via Decoupling Optimization—0
Learning Segmented 3D Gaussians via Efficient Feature Unprojection for Zero-shot Neural Scene Segmentation—0
Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection—0
VLP: Vision Language Planning for Autonomous Driving—0
FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the WildCode0
FMGS: Foundation Model Embedded 3D Gaussian Splatting for Holistic 3D Scene Understanding—0
Going Beyond Multi-Task Dense Prediction with Synergy Embedding Models—0
Unsupervised 3D Structure Inference from Category-Specific Image Collections—0
When Visual Grounding Meets Gigapixel-level Large-scale Scenes: Benchmark and Approach—0
SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes—0
PanoRecon: Real-Time Panoptic 3D Reconstruction from Monocular VideoCode0
Bilateral Adaptation for Human-Object Interaction Detection with Occlusion-Robustness—0
Towards CLIP-driven Language-free 3D Visual Grounding via 2D-3D Relational Enhancement and ConsistencyCode0
Omni-Q: Omni-Directional Scene Understanding for Unsupervised Visual Grounding—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