vit

pix2tex: Using a ViT to convert images of equations into LaTeX code.

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks

[ICLR2025, ICML2025, NeurIPS2025 Spotlight] Quantized Attention achieves speedup of 2-5x compared to FlashAttention, without losing end-to-end metrics across language, image, and video models.

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Turn any computer or edge device into a command center for your computer vision projects.

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

[CVPR 2025 Highlight] Official code and models for Encoder-only Mask Transformer (EoMT).

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

My implementation of "Patch n’ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution"

[MedIA Journal] An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

An unofficial implementation of ViTPose [Y. Xu et al., 2022]

[ECCV 2024] Pytorch code for our ECCV'24 paper NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields

Flexible Python library providing building blocks (layers) for reproducible Transformers research (Tensorflow ✅, Pytorch 🔜, and Jax 🔜)

Combining ViT and GPT-2 for image captioning. Trained on MS-COCO. The model was implemented mostly from scratch.

CLIP-based aesthetics predictor inspired by the interface of 🤗 huggingface transformers.

This is a cross-modal benchmark for industrial anomaly detection.

A Persian Image Captioning model based on Vision Encoder Decoder Models of the transformers🤗.

[CVPR 2025 Highlight] Meta LoRA / MetaPEFT: Meta-Learning Hyperparameters for Parameter-Efficient Fine-Tuning (LoRA, Adapter, Prompt Tuning) — Automatic hyperparameter optimization via bi-level meta-learning