Smartphone Photo Scanning and Restoration
Created a semi-supervised pipeline and dataset for restoring smartphone-scanned images.
Posts by Collection
portfolio
Frozen-to-FFPE Histopathology Restoration
Developed Latent Diffusion Models with histopathology pretraining to restore frozen tissue images for diagnostic accuracy.
Blending and Retouching Photos with Color Style Transfer
Proposed a new supervised color style transfer technique based on low-level transformations.
DISC: Self-Distilled LDM for Grading Prostate Cancer
Proposed a self-distillation strategy for Latent Diffusion Models to improve the accuracy in mask-to-histopathology image translation.
publications
Respecting Low-level Components of Content with Skip Connections and Semantic Information in Image Style Transfer
ACM SIGGRAPH European Conference on Visual Media Production (CVMP), 2019
Man M. Ho (Minh-Man Ho), Jinjia Zhou, Yibo Fan
Respecting low-level components of content with skip connections and semantic information in image style transfer.
Paper | Webpage | GitHub | Demo | Comparison Video
Down-Sampling Based Video Coding with Degradation-Aware Restoration-Reconstruction Deep Neural Network
International Conference on Multimedia Modeling (MMM), 2020
Man M. Ho (Minh-Man Ho), Gang He, Zheng Wang, Jinjia Zhou
Best Paper Runner-up Award at MMM2020.
SR-CL-DMC: P-frame coding with Super-Resolution, Color Learning, and Deep Motion Compensation
Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020
Man M. Ho, Jinjia Zhou, Gang He, Muchen Li, Lei Li
Top-5 performance among teams which have submitted a factsheet on P-frame Track, CLIC2020.
Paper | Webpage | Presentation
Japanese Coins and Banknotes Recognition for Visually Impaired People
VizWiz Workshop, 2020
Huyen T. T. Bui, Man M. Ho, Xiao Peng, Jinjia Zhou
Japanese coins and banknotes recognition for visually impaired people.
Deep Preset: Blending and Retouching Photos with Color Style Transfer
Winter Conference on Applications of Computer Vision (WACV), 2021
Man M. Ho, Jinjia Zhou
Proposed a novel color style transfer method. Lightroom Preset now can be any well-retouched photos.
RR-DnCNN v2.0: Enhanced Restoration-Reconstruction Deep Neural Network for Down-Sampling Based Video Coding
IEEE Transactions on Image Processing (TIP), 2021
Man M. Ho, Jinjia Zhou, Gang He
Investigated the effect of compression degradation for training. Proposed a new learned down-sampling-based video coding framework.
Paper | Webpage | GitHub | Comparison Video
Semantic-driven Colorization
ACM SIGGRAPH European Conference on Visual Media Production (CVMP), 2021
Man M. Ho, Lu Zhang, Alexander Raake, Jinjia Zhou
Semantic-driven colorization for image and video.
Deep Photo Scan: Semi-Supervised Learning for dealing with the real-world degradation in Smartphone Photo Scanning
Winter Conference on Applications of Computer Vision (WACV), 2022
Man M. Ho, Jinjia Zhou
A promising baseline for learned smartphone-scanned photo restoration.
Text-guided Image Manipulation based on Sentence-aware and Word-aware Network
IEEE International Conference on Multimedia and Expo (ICME), 2022
Zhiqiang Zhang, Chen Fu, Man M. Ho, Jinjia Zhou, Ning Jiang, Wenxin Yu
Text-guided image manipulation based on sentence-aware and word-aware network.
On Pre-chewing Compression Degradation for Learned Video Compression
IEEE International Conference on Visual Communications and Image Processing (VCIP), 2022
Man M. Ho, Heming Sun, Zhiqiang Zhang, Jinjia Zhou
Pre-chewing compression degradation for learned video compression.
Interactive Image Manipulation with Complex Text Instructions
Winter Conference on Applications of Computer Vision (WACV), 2023
Ryugo Morita, Zhiqiang Zhang, Man M. Ho, Jinjia Zhou
Interactive image manipulation with complex text instructions.
HistoEM: A Pathologist-Guided and Explainable Workflow Using Histogram Embedding for Gland Classification
Modern Pathology, 2024
Alessandro Ferrero, Elham Ghelichkhan, Hamid Manoochehri, Man M. Ho, Daniel J. Albertson, Benjamin J. Brintz, Tolga Tasdizen, Ross T. Whitaker, and Beatrice S. Knudsen
A pathologist-guided and explainable workflow using histogram embedding for gland classification.
DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Grading
IEEE International Symposium on Biomedical Imaging (ISBI), 2024
Man M. Ho, Elham Ghelichkhan, Yosep Chong, Yufei Zhou, Beatrice S. Knudsen, and Tolga Tasdizen
Developed Latent Diffusion Models (LDMs) to generate high-fidelity histopathology images for training prostate cancer grading models.
F2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE Translation
Winter Conference on Applications of Computer Vision (WACV), 2025
Man M. Ho, Shikha Dubey, Yosep Chong, Beatrice S. Knudsen, and Tolga Tasdizen
Developed LDMs with Parameter-Efficient Fine-Tuning (PEFT) and Histopathology Pre-Trained Embeddings for translating low-quality frozen section images to high-quality FFPE images.
CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification
Medical Image Analysis, 2025
Bodong Zhang, Hamid Manoochehri, Man M. Ho, Fahimeh Fooladgar, Yosep Chong, Beatrice S. Knudsen, Deepika Sirohi, and Tolga Tasdizen
Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification.
DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer
Medical Imaging with Deep Learning (MIDL), 2025
Xiaoya Tang, Bodong Zhang, Man M. Ho, Beatrice S. Knudsen, Tolga Tasdizen
Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer.
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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