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Depth Prediction

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Showing 301–350 of 422 papers

TitleStatusHype
Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation—0
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry—0
Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry—0
Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages—0
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction—0
RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion—0
RigNet: Repetitive Image Guided Network for Depth Completion—0
UniUIR: Considering Underwater Image Restoration as An All-in-One Learner—0
Robust Full-FoV Depth Estimation in Tele-wide Camera System—0
Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies—0
Robust Self-Supervised Extrinsic Self-Calibration—0
Deep Planar Parallax for Monocular Depth Estimation—0
APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation—0
Scale-aware direct monocular odometry—0
SceneScape: Text-Driven Consistent Scene Generation—0
SDC-Depth: Semantic Divide-and-Conquer Network for Monocular Depth Estimation—0
DeepLens: Shallow Depth Of Field From A Single Image—0
Wavelet Feature Maps Compression for Low Bandwidth Convolutional Neural Networks—0
Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications—0
Self-supervised 3D Object Detection from Monocular Pseudo-LiDAR—0
Self-supervised Event-based Monocular Depth Estimation using Cross-modal Consistency—0
Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy—0
Self-supervised Learning for Single View Depth and Surface Normal Estimation—0
Deep feature fusion for self-supervised monocular depth prediction—0
Self-Supervised Learning of Depth and Camera Motion from 360° Videos—0
Data-Driven Method for Enhanced Corrosion Assessment of Reinforced Concrete Structures—0
Web Stereo Video Supervision for Depth Prediction from Dynamic Scenes—0
Self-supervised Pretraining and Finetuning for Monocular Depth and Visual Odometry—0
Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery—0
Cross-Dimensional Refined Learning for Real-Time 3D Visual Perception from Monocular Video—0
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds—0
Semantics-Driven Unsupervised Learning for Monocular Depth and Ego-Motion Estimation—0
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks—0
A Novel 3D-UNet Deep Learning Framework Based on High-Dimensional Bilateral Grid for Edge Consistent Single Image Depth Estimation—0
Convolutional neural network-based regression for depth prediction in digital holography—0
Contrastive Unsupervised Learning of World Model with Invariant Causal Features—0
An evaluation of deep learning models for predicting water depth evolution in urban floods—0
Consistent Depth Prediction under Various Illuminations using Dilated Cross Attention—0
SimpleMapping: Real-Time Visual-Inertial Dense Mapping with Deep Multi-View Stereo—0
Consistent Depth Prediction for Transparent Object Reconstruction from RGB-D Camera—0
Simplify Implant Depth Prediction as Video Grounding: A Texture Perceive Implant Depth Prediction Network—0
Simultaneous Localization And Mapping with depth Prediction using Capsule Networks for UAVs—0
Consistent Depth of Moving Objects in Video—0
Single Image Depth Prediction Made Better: A Multivariate Gaussian Take—0
Connecting the Dots: Learning Representations for Active Monocular Depth Estimation—0
CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth—0
SLAM Endoscopy enhanced by adversarial depth prediction—0
Sparse2Dense: From direct sparse odometry to dense 3D reconstruction—0
Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation—0
Unsupervised Monocular Depth Prediction for Indoor Continuous Video Streams—0
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