Approximating a 3DCNN with a 2DCNN
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Updated
Jul 13, 2020 - Python
Approximating a 3DCNN with a 2DCNN
[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images
[ICLR 2021] Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)
[ICASSP'22] Integer-only Zero-shot Quantization for Efficient Speech Recognition
[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization
[ECCV 2022] Official implementation of the paper "DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation"
Official PyTorch implementation of our ECCV 2022 paper "Sliced Recursive Transformer"
Reference implementation for Blueprint Separable Convolutions (CVPR 2020)
NeurIPS 2019 MicroNet Challenge
Finding Storage- and Compute-Efficient Convolutional Neural Networks
Hypercomplex Neural Networks with PyTorch
Library for Structured Matrices (approximation methods and structured layers for neural networks)
[ICML'21 Oral] I-BERT: Integer-only BERT Quantization
Code and resources on scalable and efficient Graph Neural Networks
[KDD'22] Learned Token Pruning for Transformers
Embedded and mobile deep learning research resources
Official pytorch implementation for PSUMNet for efficient skeleton action recognition
DiSK: Distilling Scaffolded Knowledge from Teacher to Student.
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
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