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 626–650 of 1723 papers

TitleStatusHype
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth EstimationCode0
Grid-augmented vision: A simple yet effective approach for enhanced spatial understanding in multi-modal agentsCode0
Continual Learning of Unsupervised Monocular Depth from VideosCode0
MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and ClassificationCode0
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation dataCode0
Constructing a Visual Relationship Authenticity DatasetCode0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep ThinkingCode0
NextStop: An Improved Tracker For Panoptic LIDAR Segmentation DataCode0
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene UnderstandingCode0
MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic ScenariosCode0
MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and ModalitiesCode0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object ExchangeCode0
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond AberrationsCode0
MC-PanDA: Mask Confidence for Panoptic Domain AdaptationCode0
General-Purpose Deep Point Cloud Feature ExtractorCode0
Attend, Infer, Repeat: Fast Scene Understanding with Generative ModelsCode0
Hierarchical Spatial Proximity Reasoning for Vision-and-Language NavigationCode0
Matterport3D: Learning from RGB-D Data in Indoor EnvironmentsCode0
Generalizing Surgical Instruments Segmentation to Unseen Domains with One-to-Many SynthesisCode0
METEOR Guided Divergence for Video CaptioningCode0
Model-based inexact graph matching on top of CNNs for semantic 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