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👋 Hi,

I’m Frank Wu

Education

  • Huazhong University of Science and Technology (bachelor)
  • Shanghai Jiao Tong University (master)

Interests

  • 👀 I specialize in research related to deep learning and its applications in image processing, particularly in semantic segmentation, instance segmentation, weakly- and semi-supervised segmentation algorithms, and 3D segmentation.

  • 🌱 Currently, I am focusing on 3D mesh segmentation, exploring both fully supervised and weakly-supervised approaches.

  • 👀 Additionally, I am actively learning about NeRF (Neural Radiance Fields) and its applications in computer vision.

  • 🌱 I am hoping to secure a PhD offer from North America to further advance my research in these areas.

  • 📫 [email protected] OR [email protected]

Frank Wu's Projects

cct icon cct

:page_facing_up: Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CVPR 2020).

cswin-transformer icon cswin-transformer

CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped, CVPR 2022

labelme icon labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

maskrcnn-benchmark icon maskrcnn-benchmark

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

mc-net icon mc-net

Official Code for our paper "Mutual Consistency Learning for Semi-supervised Medical Image Segmentation"

polyp-pvt icon polyp-pvt

Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers

pranet icon pranet

PraNet: Parallel Reverse Attention Network for Polyp Segmentation, MICCAI 2020 (Oral). Code using Jittor Framework is available.

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