NovaMind-Z

NovaMind-Z's Stars

• peteanderson80/bottom-up-attention

  Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

  Language:Jupyter Notebook1.4k26117378

• google-research/fixmatch

  A simple method to perform semi-supervised learning with limited data.

  Language:Python1.1k1963177

• sthalles/PyTorch-BYOL

  PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

  Language:Jupyter Notebook480121372

• eliasson/pieces

  An experimental BitTorrent client in Python 3.5

  Language:Python2439267

• stanfordnlp/stanfordnlp

  [Deprecated] This library has been renamed to "Stanza". Latest development at: https://github.com/stanfordnlp/stanza

  Language:Python116141026

• xiaosu-zhu/McQuic

  Repository of CVPR'22 paper "Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression"

  Language:Python1111814

• WangGodder/deep-cross-modal-hashing

  Deep learning cross modal hashing in PyTorch

  Language:Python10232425

• qilong-zhang/Patch-wise-iterative-attack

  Patch-wise iterative attack (accepted by ECCV 2020) to improve the transferability of adversarial examples.

  Language:Python895620

• iacercalixto/visualsem

  Repository for VisualSem: a high-quality knowledge graph to support research in vision and language.

  Language:Python87387

• Wangt-CN/MTFN-RR-PyTorch-Code

  The offical code for paper "Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking", ACM Multimedia 2019 Oral

  Language:Python685818

• xinyandai/product-quantization

  Implementation of vector quantization algorithms, codes for Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search.

  Language:Python575115

• qilong-zhang/Pytorch_Universal-adversarial-perturbation

  A PyTorch implementation of universal adversarial perturbation (UAP) which is more easy to understand and implement.

  Language:Python53255

• retrieval-cfm/Archives

  Language:Python3