[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
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Updated
Oct 3, 2023 - Python
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
Pytorch implementation of our paper accepted by CVPR 2020 (Oral) -- HRank: Filter Pruning using High-Rank Feature Map
volksdep is an open-source toolbox for deploying and accelerating PyTorch, ONNX and TensorFlow models with TensorRT.
Riverbed Community Toolkit is a public toolkit for Riverbed Solutions engineering and integration
A package for processing signals recorded using wearable sensors, such as Electrocardiogram (ECG), Photoplethysmogram (PPG), Electrodermal activity (EDA) and 3-axis acceleration (ACC).
Benchmarking suite to evaluate 🤖 robotics computing performance. Vendor-neutral. ⚪Grey-box and ⚫Black-box approaches.
动手学习TVM核心原理教程
[CVPR 2024 Highlight] DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models
Post processing routines for analysing PTV data.
pymotiontracker is a Python 3 library to read from an MPU6050 (accelerometer + gyroscope) Bluetooth module
Implementation of "Fully Learnable Group Convolution for Acceleration of Deep Neural Networks", CVPR'19
TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding
[NeurIPS 2022] Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
Caffe Computation Graph Optimization.
PyTorch implementation of "Dynamic Structure Pruning for Compressing CNNs" (AAAI 2023 Oral)
CircuitPython I2C driver for MPU9250 9-axis motion tracking device
Pytorch implementation of our paper accepted by ECCV2022 -- Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks
Acceleration and Compression of DeepFwFM.
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