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GenTron: Diffusion Transformers for Image and Video Generation
CVPR'24 Project
PIXART-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
ICLR'24 Spotlight Project and Code
Multi-Modality Arena: an evaluation platform for large multi-modality models
Embodiedgpt: Vision-language pre-training via embodied chain of thought
NeurIPS'23 Porject and Code
RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis
Biography
- $\color{green}{\mathcal{N}ew!}$ We’re actively recruiting Postdocs, PhDs, and RAs. Please drop me an email via pluo.lhi@gmail.com.
- 2024-03: Two papers will be presented in SIGGRAPH'24, eight papers in ICLR'24 (two spotlights), eight papers in CVPR'24.
- 2024-01: Received the prestigious HKU Outstanding Young Researcher Award 2023. Enjoy the video!
- 2023-10: DiffusionDet was nominated for the Best Paper Final List (17/8260, 0.2%) at ICCV 2023. PVT v2 received the Best Paper Runner-up of the Year 2023 at the Computaional Visual Media Journal (CVMJ). SegFormer and PVT v1 received the Outstanding Young Paper Awards at the World AI Conference (WAIC) 2023.
- 2023-06: Ten papers will be presented in CVPR'23, eleven in ICCV'23, three in ICLR'23, three in ICML'23, six in NeurIPS'23.
- 2022-05: Our paper “Compression of Generative Pre-trained Language Models via Quantization” received ACL 2022 Outstanding Paper Award. 5 papers were presented in ICLR 2022 (CycleMLP is an oral presentation, accepted rate 1.6%), 7 papers in CVPR 2022 (2 oral presentation), 3 papers will be presented in ICML 2022.
My researches aim at (1) developing Differentiable/ Meta/ Reinforcement Learning algorithms that endow machines and devices to solve complex tasks with larger autonomy, (2) understanding foundations of deep learning algorithms, and (3) enabling applications in Machine Vision and Artificial Intelligence such as text to image/video generation, 3D vision, scene and video understanding, and medical image analysis.
Biography
Ping Luo is an Associate Professor in the Department of Computer Science at the University of Hong Kong, an Associate Director of the HKU Musketeers Foundation Institute of Data Science (HKU IDS), and a Deputy Director of the Joint Research Lab of HKU and Shanghai AI Lab. He obtained his Ph.D. in Information Engineering from the Chinese University of Hong Kong in 2014, under the supervision of Prof. Xiaoou Tang (founder of SenseTime) and Prof. Xiaogang Wang. Before joining HKU in 2019, he was a Research Director in SenseTime. He has published 100+ papers in international conferences and journals such as TPAMI, ICML, ICLR, NeurIPS, and CVPR, with over 50,000 citations on Google Scholar. He was awarded the 2015 AAAI Easily Accessible Paper, nominated for the 2022 Computational Visual Media Journal's Best Paper of the Year, won the 2022 ACL Outstanding Paper, the 2023 World Artificial Intelligence Conference (WAIC) Outstanding Papers, and was a candidate for the Best Paper at ICCV’23. He was recognized as one of the innovators under 35 in the Asia-Pacific region by the MIT Technology Review (MIT TR35) in 2020. He has mentored 30 Ph.D. students, many of whom have received significant awards such as the Nvidia Fellowship, Baidu Fellowship, WAIC Yunfan Award, etc.
Recent Publications
News&Talks
Recruitment and Opportunities
Understanding Normalization in Deep Learning
Learning-to-Learn-to-Normalize: Algorithms, Applications and Theory
浅谈深度学习：归一化中的正则与泛化
WIDER Face and Pedestrian Challenge 2018
Principal Investigator
Ping Luo
Associate Professor, Computer Science, The University of Hong Kong
Advisory Committee
Wenping Wang
Professor, IEEE Fellow
Xiaoou Tang
In Forever Memory of Professor Sean Tang
PhD Candidates
Anran Liu
PhD, since 2019 (HKPFS), co-supervised with Prof. Wenping Wang
Low-Level Vision, Deep Learning
Chaofan Tao
PhD, since 2020. webpage Co-supervised with Prof. Ngai Wong
Model Compression and Acceleration, Hardware-efficient AI
Chongjian GE
PhD, since 2020 (HKPFS). webpage
Object Detection, Visual Question Answering, Deep Learning
Jiannan Wu
PhD, since 2020 (HKPFS). webpage
Math Exercise Representation, Visual Question Answering, Deep Learning
Peng Xu
PhD, since 2021 (HKU-SUSTech Joint PhD Programme). Co-supervised with Prof. Fengwei An
Computer Vision, Edge Computing
Qiushan Guo
PhD, since 2020. Co-supervised with Prof. Yizhou Yu
Knowledge Distillation, Object Detection, Deep Learning
Runjian Chen
PhD, since 2021 (HKPFS). webpage
Representation Learning, Deep Learning, Autonomous Driving, 3D Computer Vision
Teng Wang
PhD, since 2020 (HKU-SUSTech Joint PhD Programme). Co-supervised with Prof. Feng Zheng
Neural Architecture Search, Deep Learning
Yuheng Lei
PhD (HKPFS), 2023-, webpage
Embodied AI, Reinforcement Learning, Robotics, Autonomous Driving
Zhanglin Peng
PhD, since 2020 (University Fellowship UPF). webpage Co-supervised with Prof. Wenping Wang
Normalization Methods, Image Recognition, Object Detection and Semantic Segmention, Image Demosaicing and Denoising, Deep Learning
Zhixuan Liang
PhD, since 2022 (HKPFS). webpage
Active Learning and Incremental Learning, Open World Detection, Autonomous Driving
Alumni
Nenglun Chen
PhD, 2017-2023. webpage Co-supervised with Prof. Wenping Wang
Geometric Deep Learning, Multimodal Learning
Wenhai Wang
RA, 2019-2020. webpage
Text Understanding, Instance-level Detection and Segmentation, Deep Learning
Wenqi Shao
PhD, since 2018. webpage Co-supervised with Prof. Xiaogang Wang
Normalization Methods, Efficient Neural Nets, Deep Learning
Xingang Pan
PhD, 2017-2021. webpage Co-supervised with Prof. Xiaoou Tang
Generative Models, Deep Learning
Zhaoyang Zhang
PhD, 2019-2023. webpage Co-supervised with Prof. Xiaogang Wang
Efficient Algorithm Design, Optimization, Computer Vision
Zhouxia Wang
PhD, 2020-2023. webpage Co-supervised with Prof. Wenping Wang
Exposure Bracketing Selection, Multi-exposure Fusion and Image Denoising, Image Recognition and Object Detection, Deep Learning
Projects
DeepFashion2
DeepFashion second edition with a full-spectrum of fashion image analyses.
Switchable Normalization
Meta-learning to learn normalization method for each hidden layer in ConvNet.
Regularization in BN
Understanding Batch Normalization in deep learning.
Traffic Scene Segmentation
Fast scene segmentation by layer cascade deep networks.
Lane Detection
Spatial CNN for Lane Detection.
Understanding Normalization
Understanding Normalization Methods in Deep Learning.
Face Image Generation
Image Generation via GANs.
CUImage Dataset
A large-scale dataset for learning general visual representation.
Face Relationship
A large-scale face relationship dataset.
Language Guided Image Segmentation
Joint learning image and language.
WIDERFace
A large-scale dense face detection challenge.
DeepFashion
DeepFashion first edition.
Face Model Compression
An extremely fast face recognition system .
Comprehensive Car
A large-scale car re-identification benchmark.
CelebA
Face celebrity dataset for attribute recognition and GANs.
Deep Learning MRF for Image Segmentation
Deep learning for semantic image segmentation.
Pedestrian Detection
Pedestrian Detection via Rich Supervisions.
Pedestrian Parsing
A pedestrian parsing benchmark.
Contact
- (+852) 2859 2190
- Room 326, Department of Computer Science, Chow Yei Ching Building, The Univeristy of Hong Kong, Pokfulam Road, Hong Kong,