leoluopy / circle-loss-demonstrationLinks
this is a pytorch simple demonstration of CVPR2020 circle loss
☆13Updated 4 years ago
Alternatives and similar repositories for circle-loss-demonstration
Users that are interested in circle-loss-demonstration are comparing it to the libraries listed below
Sorting:
- ☆166Updated last year
- ☆66Updated last year
- 天池淘宝直播商品识别大赛 复赛第7名方案☆38Updated 5 years ago
- 这里是改进了pytorch的DataParallel, 用来平衡第一个GPU的显存使用量☆232Updated 4 years ago
- A light-weight script for maintaining a LOT of machine learning experiments.☆92Updated 2 years ago
- 2020 DIGIX GLOBAL AI CHALLENGE - Digital Device Image Retrieval - Top2 WEARE队☆65Updated 4 years ago
- ☆60Updated 2 years ago
- Focal loss for multiple class classification☆83Updated 4 years ago
- A brief of TorchScript by MNIST☆112Updated 3 years ago
- PyTorch Dataset Rank Dataset☆43Updated 4 years ago
- RepVGG TensorRT int8 量化,实测推理不到1ms一帧!☆62Updated 4 years ago
- ccks2022 task9 subtask2 商品同款识别☆45Updated 2 years ago
- Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.☆169Updated 2 years ago
- ☆90Updated 2 years ago
- QQ浏览器2021AI算法大赛赛道一 第1名 方案☆267Updated 3 years ago
- [ECCV 2020 Workshop] VIPirios Object Detection Champion☆44Updated 2 years ago
- This project aims to explore the deployment of Swin-Transformer based on TensorRT, including the test results of FP16 and INT8.☆170Updated 2 years ago
- centernet_simple☆24Updated 5 years ago
- 科大讯飞x光安检图像识别1st☆17Updated 4 years ago
- 一个多模态内容理解算法框架,其中包含数据处理、预训练模型、常见模型以及模型加速等模块。☆320Updated 3 years ago
- United Perception☆435Updated 2 years ago
- NVIDIA-阿里2021 TRT比赛 `二等奖` 代码提交 团队:美迪康 AI Lab☆171Updated 3 years ago
- (ECCV 22 Oral) ObjectBox: From Centers to Boxes for Anchor-Free Object Detection☆134Updated 2 years ago
- 2022天池商品标志目标检测☆87Updated 3 years ago
- 论文阅读以及笔记☆31Updated 4 years ago
- ☆882Updated last year
- The 1st place solution of track2 (Vehicle Re-Identification) in the NVIDIA AI City Challenge at CVPR 2021 Workshop.☆126Updated 4 years ago
- In CVPR 2020 AliProducts Challenge: Large-scale Product Recognition, we got error rate 0.099 and ranked No.6. The model will get higher s…☆94Updated 2 years ago
- 多模态 MM +Chat 合集☆275Updated 2 weeks ago
- Pytorch implementation of NetVlad for classification on UCF101☆27Updated 5 years ago