Source code of paper: (not available now)
☆92Nov 25, 2018Updated 7 years ago
Alternatives and similar repositories for Competitive-Inner-Imaging-SENet
Users that are interested in Competitive-Inner-Imaging-SENet are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A MXNet implementation of Squeeze-and-Excitation Networks (SE-ResNext, SE-Resnet, SE-Inception-v4 and SE-Inception-Resnet-v2)☆157Jul 27, 2018Updated 7 years ago
- A Gluon implement of Residual Attention Network. Best acc on cifar10-97.78%.☆107Jun 12, 2019Updated 6 years ago
- ☆229Mar 1, 2019Updated 7 years ago
- MXNet implementation of Non-Local and Squeeze-Excitation network☆24Jan 30, 2018Updated 8 years ago
- Cascade R-CNN forked from gluon-cv☆33Oct 26, 2022Updated 3 years ago
- ☆16Dec 16, 2017Updated 8 years ago
- A code gallery for person re-identification with mxnet-gluon, and I will reproduce many STOA algorithm.☆175Aug 16, 2018Updated 7 years ago
- ☆14Dec 13, 2017Updated 8 years ago
- PyTorch API for GluonCV Models☆531Nov 2, 2022Updated 3 years ago
- MXNet implementation of Graph Convolutional Neural Networks☆20Oct 8, 2018Updated 7 years ago
- A MXNet implementation of Modified CRUNet & Residual Attention Network☆67Oct 22, 2018Updated 7 years ago
- This is the proposal network for MultiPerson Pose Estimation.☆14Oct 21, 2017Updated 8 years ago
- Convolutional Neural Networks with Alternately Updated Clique (to appear in CVPR 2018)☆327Jul 5, 2018Updated 7 years ago
- Tutorial Materials for ICCV19☆278Oct 9, 2022Updated 3 years ago
- Code and Pretrained model for IGCV3☆189Oct 22, 2018Updated 7 years ago
- A Gluon implementation of Mnasnet☆60Dec 27, 2018Updated 7 years ago
- [ECCV 2018] Sparsely Aggreagated Convolutional Networks https://arxiv.org/abs/1801.05895☆123Oct 10, 2018Updated 7 years ago
- mxnet version batch hard triplet loss☆13Aug 30, 2018Updated 7 years ago
- CVPR18 Paper: Multi-scale Location-aware Kernel Representation for Object Detection☆106Jun 16, 2021Updated 4 years ago
- The code of Switchable Normalization for object detection based on Detectron.pytorch.☆78Jul 26, 2018Updated 7 years ago
- Gluon implement of Kaggle cifar10 competition☆50Nov 7, 2017Updated 8 years ago
- PyTorch implementation of PNASNet-5 on ImageNet☆320Aug 4, 2022Updated 3 years ago
- Domain Agnostic Normalization layer for Unsupervised Domain Adaptation☆11Dec 8, 2022Updated 3 years ago
- Deep Learning Study with Gluon☆59Jun 3, 2018Updated 7 years ago
- implementation for paper "ShelfNet for fast semantic segmentation"☆252Feb 27, 2021Updated 5 years ago
- this repo attemps to reproduce DSOD: Learning Deeply Supervised Object Detectors from Scratch use gluon reimplementation☆14Aug 18, 2018Updated 7 years ago
- 使用mxnet编写的kaggle CIFAR10比赛的代码☆68May 26, 2018Updated 7 years ago
- DeepLab v3+ in MXNet Gluon☆59Sep 30, 2018Updated 7 years ago
- A python version of Spatiotemporal Multiplier Networks based on mxnet.☆10Jan 2, 2018Updated 8 years ago
- Code for the ECCV 2018 paper "Pairwise Confusion for Fine-Grained Visual Classification"☆201Sep 11, 2018Updated 7 years ago
- Semantic Image Segmentation by Scale-Adaptive Networks (TIP 2019)☆43Sep 14, 2019Updated 6 years ago
- ☆18Jan 9, 2018Updated 8 years ago
- Code for the Pose Residual Network introduced in 'MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network' paper htt…☆285Aug 6, 2021Updated 4 years ago
- Code for "Ordinal Depth Supervision for 3D Human Pose Estimation", CVPR 2018☆112Jun 21, 2018Updated 7 years ago
- PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)☆126Sep 6, 2018Updated 7 years ago
- Lookahead Optimizer: k steps forward, 1step back for MXNet☆21Jun 28, 2020Updated 5 years ago
- Reproduction of MobileNetV2 using MXNet☆128Mar 15, 2019Updated 7 years ago
- PyTorch Implementation of Compact Generalized Non-local Network [NIPS'18]☆258Feb 13, 2021Updated 5 years ago
- Improving Object Detection from Scratch via Gated Feature Reuse (BMVC 2019)☆65May 9, 2020Updated 5 years ago