Computer Vision – ECCV 2020 Workshops

W01 - Adversarial Robustness in the Real World.- A Deep Dive into Adversarial Robustness in Zero-Shot Learning.- Towards Analyzing Semantic Robustness of Deep Neural Networks.- Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses.- Deep k-NN Defense Against Clean-label Data Poisoning Attacks.- Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings.- Adversarial Shape Perturbations on 3D Point Clouds.- Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks.- Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency Map Comparison.- Adversarial Robustness of Open-set Recognition: Face Recognition and Person Re-identification.- WaveTransform: Crafting Adversarial Examples via Input Decomposition.- Robust Super-Resolution of Real Faces using Smooth Features.- Improved Robustness to Open Set Inputs via Tempered Mixup.- Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers.- Adversarial Attack on Deepfake Detection using RL based Texture Patches.- W02 - BioImage Computation.- A Subpixel Residual U-Net and Feature Fusion Preprocessing for Retinal Vessel Segmentation.- Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation.- Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer.- Bionic Tracking: Using Eye Tracking to Track Biological Cells in Virtual Reality.- Cardiac MR Image Sequence Segmentation with Temporal Motion Encoding.- Classifying Nuclei Shape Heterogeneity in Breast Tumors with Skeletons.- DenoiSeg: Joint Denoising and Segmentation.- DoubleU-Net: Colorectal Cancer Diagnosis and Gland Instance Segmentation with Text-Guided Feature Control.- Dynamic Image for 3D MRI Image Alzheimer's Disease Classification.- Feedback Attention for Cell Image Segmentation.- Improving Blind Spot Denoising for Microscopy.- Learning toRestore ssTEM Images from Deformation and Corruption.- Learning to Segment Microscopy Images with Lazy Labels.- Multi-CryoGAN: Reconstruction of Continuous Conformations in Cryo-EM Using Generative Adversarial Networks.- Probabilistic Deep Learning for Instance Segmentation.- Registration of Multi-modal Volumetric Images by Establishing Cell Correspondence.- W2S: Microscopy Data with Joint Denoising and Super-Resolution for Wide field to SIM Mapping.- W03 - Egocentric Perception, Interaction and Computing.- An investigation of Deep Visual Architectures based on Preprocess Using the Retinal Transform.- Data Augmentation Techniques for the Video Question Answering Task.- W05 - Eye Gaze in VR, AR, and in the Wild.- Efficiency in Real-time Webcam Gaze Tracking.- Hierarchical HMM for Eye Movement Classification.- Domain Adaptation for Eye Segmentation.- EyeSeg: Fast and Efficient Few-Shot Semantic Segmentation.- W10 - TASK-CV Workshop and VisDA Challenge.- Class-imbalanced Domain Adaptation: An Empirical Odyssey.- Sequential Learning for Domain Generalization.- Generating Visual and Semantic Explanations with Multi-task Network.- SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection.- Using Sentences as Semantic Representations in Large Scale Zero-Shot Learning.- Adversarial Transfer of Camera Pose Regression.- Disentangled Image Generation for Unsupervised Domain Adaptation.- Domain Generalization using Shape Representation.- Bi-Dimensional Feature Alignment for Cross-Domain Object Detection.- Bayesian Zero-Shot Learning.- Self-Supervision for 3D Real-World Challenges.- Diversified Mutual Metric Learning.- Domain Generalization vs Data Augmentation: an Unbiased Perspective.- W11 - Bodily Expressed Emotion Understanding.- Panel: Bodily Expressed Emotion Understanding Research: A Multidisciplinary Perspective.- Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss.- Noisy Student Training using Body Language Dataset Improves Facial Expression Recognition.- Emotion Embedded Pose Generation.- Understanding Political Communication Styles in Televised Debates via Body Movements.