Deep Ranking for Image Zero-Shot Multi-Label Classification 6549-6560 A Novel Deep Learning Pipeline for Retinal Vessel Detection In Fluorescein Angiography 6561-6573 A Unified Deep Model for Joint Facial Expression Recognition, Face Synthesis, and Face Alignment 6574-6589 FADE: Feature Aggregation for Depth Estimation With Multi-View Stereo 6590-6600 Polarimetric SAR Image Semantic Segmentation With 3D Discrete Wavelet Transform and Markov Random Field 6601-6614 Robust Estimation of Absolute Camera Pose via Intersection Constraint and Flow Consensus 6615-6629 Light Field Synthesis by Training Deep Network in the Refocused Image Domain 6630-6640 SAR Image Speckle Filtering With Context Covariance Matrix Formulation and Similarity Test 6641-6654 Textual-Visual Reference-Aware Attention Network for Visual Dialog 6655-6666 Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks 6667-6679 Structured Dictionary Learning for Image Denoising Under Mixed Gaussian and Impulse Noise 6680-6693 Long-Term Tracking With Deep Tracklet Association 6694-6706 Interpret Neural Networks by Extracting Critical Subnetworks 6707-6720 Multi-Exponential Transverse Relaxation Times Estimation From Magnetic Resonance Images Under Rician Noise and Spatial Regularization 6721-6733 An Unordered Image Stitching Method Based on Binary Tree and Estimated Overlapping Area 6734-6744 Self-Supervised Feature Augmentation for Large Image Object Detection 6745-6758 Removing Arbitrary-Scale Rain Streaks via Fractal Band Learning With Self-Supervision 6759-6772 PMHLD: Patch Map-Based Hybrid Learning DehazeNet for Single Image Haze Removal 6773-6788 Group Feedback Capsule Network 6789-6799 Crowd Counting Via Cross-Stage Refinement Networks 6800-6812 Hyperspectral Image Compressive Sensing Reconstruction Using Subspace-Based Nonlocal Tensor Ring Decomposition 6813-6828 MV-GNN: Multi-View Graph Neural Network for Compression Artifacts Reduction 6829-6840 Integrating Neural Networks Into the Blind Deblurring Framework to Compete With the End-to-End Learning-Based Methods 6841-6851 Single Image Deraining Using Bilateral Recurrent Network 6852-6863 www.signalprocessingsociety.org [12] AUGUST 2020https://dx.doi.org/10.1109/TIP.2020.2991527 https://dx.doi.org/10.1109/TIP.2020.2991530 https://dx.doi.org/10.1109/TIP.2020.2991549 https://dx.doi.org/10.1109/TIP.2020.2991883 https://dx.doi.org/10.1109/TIP.2020.2992177 https://dx.doi.org/10.1109/TIP.2020.2992177 https://dx.doi.org/10.1109/TIP.2020.2992336 https://dx.doi.org/10.1109/TIP.2020.2992354 https://dx.doi.org/10.1109/TIP.2020.2992883 https://dx.doi.org/10.1109/TIP.2020.2992888 https://dx.doi.org/10.1109/TIP.2020.2992893 https://dx.doi.org/10.1109/TIP.2020.2992895 https://dx.doi.org/10.1109/TIP.2020.2993073 https://dx.doi.org/10.1109/TIP.2020.2993073 https://dx.doi.org/10.1109/TIP.2020.2993114 https://dx.doi.org/10.1109/TIP.2020.2993114 https://dx.doi.org/10.1109/TIP.2020.2993134 https://dx.doi.org/10.1109/TIP.2020.2993403 https://dx.doi.org/10.1109/TIP.2020.2993406 https://dx.doi.org/10.1109/TIP.2020.2993407 https://dx.doi.org/10.1109/TIP.2020.2993931 https://dx.doi.org/10.1109/TIP.2020.2994410 https://dx.doi.org/10.1109/TIP.2020.2994411 https://dx.doi.org/10.1109/TIP.2020.2994411 https://dx.doi.org/10.1109/TIP.2020.2994412 https://dx.doi.org/10.1109/TIP.2020.2994413 https://dx.doi.org/10.1109/TIP.2020.2994413 https://dx.doi.org/10.1109/TIP.2020.2994443 http://www.signalprocessingsociety.org