Deep Ordinal Regression Network for Monocular Depth Estimation

Fu, Huan, Gong, Mingming, Wang, Chaohui, Batmanghelich, Kayhan, Tao, Dacheng·2018·2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Cited by (1,003)

Items 901–1,000 of 1,003

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  2. Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications
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  5. Weakly Supervised Monocular 3D Object Detection by Spatial-Temporal View Consistency
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  6. PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage
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  9. Towards Handling Sudden Changes in Feature Maps During Depth Estimation
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  10. Monitoring Social Distancing With Single Image Depth Estimation
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  11. Integration of ontology reasoning-based monocular cues in deep learning modeling for single image depth estimation in urban driving scenarios
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  16. Delving Into Multi-Illumination Monocular Depth Estimation: A New Dataset and Method
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  17. Self-supervised learning of monocular depth and ego-motion estimation for non-rigid scenes in wireless capsule endoscopy videos
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  18. A Contour-Aware Monocular Depth Estimation Network Using Swin Transformer and Cascaded Multiscale Fusion
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  27. Unsupervised Learning of Depth and Depth-of-Field Effect from Natural Images with Aperture Rendering Generative Adversarial Networks
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  30. Hierarchical Denoising of Ordinal Time Series of Clinical Scores
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  33. Monocular depth estimation with spatially coherent sliced network
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  40. FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation
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  41. Depth Is All You Need for Monocular 3D Detection
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  42. Virtual Occlusions Through Implicit Depth
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  43. Robust Learning for Deep Monocular Depth Estimation
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  44. Vision-only 3D Tracking for Self-Driving Cars
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  45. Geometry understanding from autonomous driving scenarios based on feature refinement
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  48. Single Image Depth Estimation Using Edge Extraction Network and Dark Channel Prior
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  49. Deformable spatial propagation network for depth completion
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  52. Geometry-aware data augmentation for monocular 3D object detection.
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