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2021yy's Projects

agriculture-vision icon agriculture-vision

[CVPR 2020 & 2021] Agriculture-Vision Dataset, Prize Challenge and Workshop: A joint effort with many great collaborators to bring Agriculture and Computer Vision/AI communities together to benefit humanity!

aimet icon aimet

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

apq icon apq

[CVPR 2020] APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

convmae icon convmae

ConvMAE: Masked Convolution Meets Masked Autoencoders

deformable-detr icon deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

detectron2 icon detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

detr icon detr

End-to-End Object Detection with Transformers

easycv icon easycv

An all-in-one toolkit for computer vision

fairseq icon fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

haq icon haq

[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision

hawq icon hawq

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

imix icon imix

A framework for Multimodal Intelligence research from Inspur HSSLAB.

lsq-net icon lsq-net

Unofficial implementation of LSQ-Net, a neural network quantization framework

mae icon mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

mimdet icon mimdet

MIMDet: Unleashing Vanilla Vision Transformer with Masked Image Modeling for Object Detection

nncf icon nncf

Neural Network Compression Framework for enhanced OpenVINO™ inference

nniefacelib icon nniefacelib

nniefacelib是一个在海思35xx系列芯片上运行的人脸算法库

norse icon norse

Deep learning with spiking neural networks (SNNs) in PyTorch.

pytorch_resnet_cifar10 icon pytorch_resnet_cifar10

Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.

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