drprojects/superpoint_transformer
quality grade C, 62 out of 100Official PyTorch implementation of Superpoint Transformer [ICCV'23], SuperCluster [3DV'24 Oral], and EZ-SP [ICRA'26]
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Core deep-learning frameworks and libraries for pretraining and distributed training.
Signals: deep-learning, neural-network, pytorch, tensorflow, jax, distributed-training, training, deepspeed
2,694 results
Official PyTorch implementation of Superpoint Transformer [ICCV'23], SuperCluster [3DV'24 Oral], and EZ-SP [ICRA'26]
Implementation of TabTransformer, attention network for tabular data, in Pytorch
Explainability for Vision Transformers
Simple transformer implementation from scratch in pytorch. (archival, latest version on codeberg)
My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.
EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]
SwissArmyTransformer is a flexible and powerful library to develop your own Transformer variants.
[NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data.
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Implementation of various self-attention mechanisms focused on computer vision. Ongoing repository.
Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch
Attention is all you need implementation
[NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang
[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Integrate deep learning models for image classification | Backbone learning/comparison/magic modification project
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
Large-scale pretraining for dialogue
[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
Flops counter for neural networks in pytorch framework
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
Transformer: PyTorch Implementation of "Attention Is All You Need"
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
24,524 repositories in the index in total.