Generative Models

Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation ICML 2020 CompressNet: Generative Compression at Extremely Low Bitrates WACV 2020 CONAN: Complementary Pattern Augmentation for Rare Disease Detection AAAI 2020 Conditional Gaussian Distribution Learning for Open Set Recognition CVPR 2020 Conditional Generative Neural Decoding with Structured CNN Feature Prediction AAAI 2020 Conditional Neural Generation using Sub-Aspect Functions for Extractive News Summarization EMNLP 2020 Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures PGM 2020 Consistency Regularization for Generative Adversarial Networks ICLR 2020 Consistent Video Style Transfer via Compound Regularization AAAI 2020 Constraining Variational Inference with Geometric Jensen-Shannon Divergence NeurIPS 2020 ContraGAN: Contrastive Learning for Conditional Image Generation NeurIPS 2020 Contrastive Representation Distillation ICLR 2020 Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation EMNLP 2020 Controllable Person Image Synthesis With Attribute-Decomposed GAN CVPR 2020 Controllable Text Generation with Focused Variation EMNLP 2020 Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data EMNLP 2020 Controlling generative models with continuous factors of variations ICLR 2020 Controlling the Amount of Verbatim Copying in Abstractive Summarization AAAI 2020 ControlVAE: Controllable Variational Autoencoder ICML 2020 Convolutional dictionary learning based auto-encoders for natural exponential-family distributions ICML 2020 Convolutional Generation of Textured 3D Meshes NeurIPS 2020 Co-Occurrence Estimation from Aggregated Data with Auxiliary Information AAAI 2020 CookGAN: Causality Based Text-to-Image Synthesis CVPR 2020 CookGAN: Meal Image Synthesis from Ingredients WACV 2020 CoPhy: Counterfactual Learning of Physical Dynamics ICLR 2020