Jierun CHEN (陈捷润) (original) (raw)

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 CVPR 2025 (Highlight) project /pdf/Supp/ Snap Newsroom/TechCrunch We propose SnapGen, the first text-to-image model (379M) that can synthesize high-resolution images (1024x1024) on mobile devices in 1.4s, and achieve 0.66 on GenEval metric.
Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models Jierun Chen*, Fangyun Wei*, Jinjing Zhao, Sizhe Song, Bohuai Wu, Zhuoxuan Peng, S.-H. Gary Chan, Hongyang Zhang CVPR Workshop BEAM 2025 pdf /code /dataset We clean the widely-adopted RefCOCO,+,g benchmarks and introduce Ref-L4, a New REC benchmark in the LMM Era.
AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation Anil Kag, Huseyin Coskun, Jierun Chen, Junli Cao, Willi Menapace, Aliaksandr Siarohin, Sergey Tulyakov, Jian Ren NeurIPs 2024 project /pdf We introduce AsCAN, a hybrid neural network with asymmetric convolutional and transformer blocks, offering superior performance and efficiency across image recognition and generation tasks.
Target-agnostic Source-free Domain Adaptation for Regression Tasks Tianlang He, Zhiqiu Xia, Jierun Chen, Haoliang Li, S.-H. Gary Chan ICDE 2024 pdf We propose TASFAR, a novel target-agnostic source-free domain adaptation method for regression tasks.
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks Jierun Chen, Shiu-hong Kao, Hao He, Weipeng Zhuo, Song Wen, Chul-Ho Lee, S.-H. Gary Chan CVPR 2023 pdf /code We propose a simple yet fast and effective partial convolution (PConv), as well as a latency-efficient family of architectures called FasterNet.
Semi-supervised Learning with Network Embedding on Ambient RF Signals for Geofencing Services Weipeng Zhuo, Ka Ho Chiu, Jierun Chen, Jiajie Tan, Edmund Sumpena, Sangtae Ha, S.-H. Gary Chan, Chul-Ho Lee ICDE 2023 pdf /code We develop a practical geofencing system, solely based on ambient radio frequency (RF) signals, to enable applications like elderly care, dementia antiwandering, pandemic control, etc.
StableKD: Breaking Inter-block Optimization Entanglement for Stable Knowledge Distillation Shiu-hong Kao*, Jierun Chen*, S.-H. Gary Chan Preprint 2023 pdf We propose StableKD, a simple and efficient Knowledge Distillation framework that attains higher accuracy using fewer training epochs and less data.
CP-NeRF: Conditionally Parameterized Neural Radiance Fields for Cross-scene Novel View Synthesis Hao He, Yixun Liang, Shishi Xiao, Jierun Chen, Yingcong Chen Pacific Graphics 2023 pdf We propose CP-NeRF to enable training a one-for-all NeRF across diverse scenes.
FIS-ONE: Floor Identification System with One Label for Crowdsourced RF Signals Weipeng Zhuo, Ka Ho Chiu, Jierun Chen, Ziqi Zhao, S.-H. Gary Chan, Sangtae Ha, Chul-Ho Lee ICDCS 2023 pdf /code We design a floor identification system for crowdsourced RF signals in a building using only one labeled data sample from the bottom floor.
TVConv: Efficient Translation Variant Convolution for Layout-Aware Visual Processing Jierun Chen, Tianlang He, Weipeng Zhuo, Li Ma, Sangtae Ha, S.-H. Gary Chan CVPR 2022 pdf / video /code TVConv works more computation-efficient than regular convolution when dealing with layout-specific tasks, e.g., face recognition.
Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty Jierun Chen, Song Wen, S.-H. Gary Chan AAAI 2021 pdf /video We consider the ground truth uncertainty for joint demosaicking and denoising in the wild, which provides better restoration result and interpretability.

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