AntoinePlumerault / Controlling-generative-models-with-continuous-factors-of-variationsLinks
Recent deep generative models are able to provide photo-realistic images as well as visual or textual content embeddings useful to address various tasks of computer vision and natural language processing. Their usefulness is nevertheless often limited by the lack of control over the generative process or the poor understanding of the learned rep…
☆21Updated 3 years ago
Alternatives and similar repositories for Controlling-generative-models-with-continuous-factors-of-variations
Users that are interested in Controlling-generative-models-with-continuous-factors-of-variations are comparing it to the libraries listed below
Sorting:
- Datasets for new state-of-the-art challenge in disentanglement learning☆46Updated 6 years ago
- Official PyTorch implementation of Spatial Dependency Networks.☆35Updated 4 years ago
- Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding☆73Updated 4 years ago
- Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with Invertible Neural Networks☆58Updated 5 years ago
- In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…☆41Updated 4 years ago
- Official code repository for Instance Selection for GANs.☆44Updated 4 years ago
- Fine-grained ImageNet annotations☆30Updated 5 years ago
- ☆42Updated 2 years ago
- ☆50Updated 4 years ago
- Code for UAI 2020 paper "Locally Masked Convolution for Autoregressive Models"☆79Updated 5 years ago
- Code for ICML2021 paper 'Commutative Lie Group VAE for Disentanglement Learning'.☆23Updated 3 years ago
- PyTorch Implementation of cGANTransfer☆45Updated 3 years ago
- PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021☆24Updated 4 years ago
- Authors official implementation of "Big GANs Are Watching You" pre-print☆115Updated 2 years ago
- Code accompanying the NeurIPS 2020 submission "Teaching a GAN What Not to Learn."☆32Updated 4 years ago
- Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis☆25Updated 4 years ago
- Tensorflow code of the paper "Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game".☆37Updated 6 years ago
- [ICCV 2021] A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generative Modeling"☆80Updated 2 years ago
- Code for ICLR 2022 Paper, "Controlling Directions Orthogonal to a Classifier"☆35Updated 2 years ago
- ☆87Updated 3 years ago
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 5 years ago
- Visual Representation Learning Benchmark for Self-Supervised Models☆35Updated last year
- [ICLR'21] Counterfactual Generative Networks☆107Updated 4 years ago
- Code for CVPR2021 paper 'Where and What? Examining Interpretable Disentangled Representations'.☆45Updated 3 years ago
- A TensorFlow implementation of perceptual generative autoencoder (PGA).☆22Updated 5 years ago
- ☆21Updated 4 years ago
- A Disentangling Invertible Interpretation Network☆122Updated 4 years ago
- Code associated with our paper "Learning Group Structure and Disentangled Representations of Dynamical Environments"☆15Updated 3 years ago
- [CogSci'21] Study of human inductive biases in CNNs and Transformers.☆43Updated 4 years ago
- ☆83Updated 2 years ago