EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]

Embedded and mobile deep learning research resources

Code and resources on scalable and efficient Graph Neural Networks

Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

[CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework

[ICML'21 Oral] I-BERT: Integer-only BERT Quantization

[ECCV 2022] Official implementation of the paper "DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation"

Reference implementation for Blueprint Separable Convolutions (CVPR 2020)

[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

[KDD'22] Learned Token Pruning for Transformers

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

(ICLR 2024, CVPR 2024) SparseFormer

Official PyTorch implementation of our ECCV 2022 paper "Sliced Recursive Transformer"

Hypercomplex Neural Networks with PyTorch

[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images

[ICASSP'22] Integer-only Zero-shot Quantization for Efficient Speech Recognition

Official pytorch implementation for PSUMNet for efficient skeleton action recognition

Event-based neural networks

Finding Storage- and Compute-Efficient Convolutional Neural Networks

NeurIPS 2019 MicroNet Challenge