Pattern Recognition

Machine Learning and Optimization.- Sublabel-Accurate Multilabeling Meets Product Label Spaces.- InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization.- Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise.- Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data.- Revisiting Consistency Regularization for Semi-Supervised Learning.- Learning Robust Models Using the Principle of Independent Causal Mechanisms.- Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks.- Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators.- End-to-end Learning of Fisher Vector Encodings for Part Features in Fine-grained Recognition.- Investigating the Consistency of Uncertainty Sampling in Deep Active Learning.- ScaleNet: An Unsupervised Representation Learning Method for Limited Information.- Actions, Events, and Segmentation.- A New Split for Evaluating True Zero-Shot Action Recognition.- Video Instance Segmentation with Recurrent Graph Neural Networks.- Distractor-Aware Video Object Segmentation.- (SP)^2Net for Generalized Zero-Label Semantic Segmentation.- Contrastive Representation Learning for Hand Shape Estimation.- Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks.- FIFA: Fast Inference Approximation for Action Segmentation.- Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision.- A Comparative Study of PnP and Learning Approaches to Super-Resolution in a Real-World Setting.- Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing.- Spatiotemporal Outdoor Lighting Aggregation on Image Sequences.- Generative Models and Multimodal Data.- AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style.- Learning Conditional Invariance through Cycle Consistency.- CAGAN: Text-To-Image Generation with Combined Attention