Highlights
- Pro
Stars
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
AlphaFold 3 inference pipeline.
Python Sorted Container Types: Sorted List, Sorted Dict, and Sorted Set
Unbearably fast near-real-time pure-Python runtime-static type-checker.
Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.
An AI agent system for solving International Mathematical Olympiad (IMO) problems using Google's Gemini, OpenAI, and XAI APIs.
Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)
Convert torch t7 model to pytorch model and source.
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
Video Representation Learning by Dense Predictive Coding. Tengda Han, Weidi Xie, Andrew Zisserman.
Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"
Code for unsupervised learning of object landmarks as proposed in "Unsupervised Learning of Object Landmarks through Conditional Image Generation", Tomas Jakab*, Ankush Gupta*, Hakan Bilen, Andrea …
Code for the paper: "SuS-X: Training-Free Name-Only Transfer of Vision-Language Models" [ICCV'23]
Pure Python dashboard for monitoring deep learning experiments (like TensorBoard for PyTorch/JAX/etc, without a browser)
Can GPT-4 Perform Neural Architecture Search?
BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues, ECCV 2020
[NeurIPS 2022 Spotlight] RLIP: Relational Language-Image Pre-training and a series of other methods to solve HOI detection and Scene Graph Generation.
Minimal API for receptive field calculation in PyTorch
Seeing Wake Words: Audio-visual Keyword Spotting
[CVPRW'22] Unsupervised Salient Object Detection With Spectral Cluster Voting
[NeurIPS'22] ReCo: Retrieve and Co-segment for Zero-shot Transfer
Cross Modal Retrieval with Querybank Normalisation
Implementation of "Audio Retrieval with Natural Language Queries: A Benchmark Study".
Sign Language Segmentation with Temporal Convolutional Networks (ICASSP'21) and Sign Segmentation with Changepoint-Modulated Pseudo-Labelling (CVPRW'21)
PyTorch implementation of Mahendran & Vedaldi, 2015: "Understanding Deep Image Representations by Inverting Them"
A Pytorch implementation of https://arxiv.org/abs/1810.12348.