Cheng, Kwang-Ting

29 publications

ICLR 2025 Memory Efficient Transformer Adapter for Dense Predictions Dong Zhang, Rui Yan, Pingcheng Dong, Kwang-Ting Cheng

CVPR 2025 SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training Jierun Chen, Dongting Hu, Xijie Huang, Huseyin Coskun, Arpit Sahni, Aarush Gupta, Anujraaj Goyal, Dishani Lahiri, Rajesh Singh, Yerlan Idelbayev, Junli Cao, Yanyu Li, Kwang-Ting Cheng, S.-H. Gary Chan, Mingming Gong, Sergey Tulyakov, Anil Kag, Yanwu Xu, Jian Ren

CVPRW 2024 CMOSE: Comprehensive Multi-Modality Online Student Engagement Dataset with High-Quality Labels Chi-Hsuan Wu, Shih-Yang Liu, Xijie Huang, Xingbo Wang, Rong Zhang, Luca Minciullo, Wong Kai Yiu, Kenny Kwan, Kwang-Ting Cheng

AAAI 2024 DTMFormer: Dynamic Token Merging for Boosting Transformer-Based Medical Image Segmentation Zhehao Wang, Xian Lin, Nannan Wu, Li Yu, Kwang-Ting Cheng, Zengqiang Yan

ICML 2024 DoRA: Weight-Decomposed Low-Rank Adaptation Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin, Pavlo Molchanov, Yu-Chiang Frank Wang, Kwang-Ting Cheng, Min-Hung Chen

TMLR 2024 Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precision Xijie Huang, Zhiqiang Shen, Pingcheng Dong, Kwang-Ting Cheng

TMLR 2024 Robust and Efficient Quantization-Aware Training via Coreset Selection Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng

IJCAI 2023 FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity Nannan Wu, Li Yu, Xuefeng Jiang, Kwang-Ting Cheng, Zengqiang Yan

ICML 2023 Oscillation-Free Quantization for Low-Bit Vision Transformers Shih-Yang Liu, Zechun Liu, Kwang-Ting Cheng

ICCV 2023 Randomized Quantization: A Generic Augmentation for Data Agnostic Self-Supervised Learning Huimin Wu, Chenyang Lei, Xiao Sun, Peng-Shuai Wang, Qifeng Chen, Kwang-Ting Cheng, Stephen Lin, Zhirong Wu

NeurIPS 2023 Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation Weihang Dai, Yao Du, Hanru Bai, Kwang-Ting Cheng, Xiaomeng Li

AAAI 2023 Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks Weihang Dai, Xiaomeng Li, Kwang-Ting Cheng

ECCV 2022 Data-Free Neural Architecture Search via Recursive Label Calibration Zechun Liu, Zhiqiang Shen, Yun Long, Eric Xing, Kwang-Ting Cheng, Chas Leichner

CVPR 2022 Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen

ICML 2022 SDQ: Stochastic Differentiable Quantization with Mixed Precision Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Hu Xianghong, Jeffry Wicaksana, Eric Xing, Kwang-Ting Cheng

AAAI 2022 Stereo Neural Vernier Caliper Shichao Li, Zechun Liu, Zhiqiang Shen, Kwang-Ting Cheng

CVPR 2022 Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing

CVPR 2021 Exploring Intermediate Representation for Monocular Vehicle Pose Estimation Shichao Li, Zengqiang Yan, Hongyang Li, Kwang-Ting Cheng

ICML 2021 How Do Adam and Training Strategies Help BNNs Optimization Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng

ICLR 2021 Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides

AAAI 2021 Partial Is Better than All: Revisiting Fine-Tuning Strategy for Few-Shot Learning Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng

CVPR 2021 S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-Bit Neural Networks via Guided Distribution Calibration Zhiqiang Shen, Zechun Liu, Jie Qin, Lei Huang, Kwang-Ting Cheng, Marios Savvides

ECCV 2020 ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng

NeurIPS 2019 Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder

CVPRW 2019 Visualizing the Decision-Making Process in Deep Neural Decision Forest Shichao Li, Kwang-Ting Cheng

ECCV 2018 Bi-Real Net: Enhancing the Performance of 1-Bit CNNs with Improved Representational Capability and Advanced Training Algorithm Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng

CVPRW 2011 Energy-Optimized Mapping of Application to Smartphone Platform - A Case Study of Mobile Face Recognition Yi-Chu Wang, Kwang-Ting Cheng

CVPR 2006 Fast Human Detection Using a Cascade of Histograms of Oriented Gradients Qiang Zhu, Mei-Chen Yeh, Kwang-Ting Cheng, Shai Avidan

ICCV 2005 Learning a Sparse, Corner-Based Representation for Time-Varying Background Modeling Qiang Zhu, Shai Avidan, Kwang-Ting Cheng