Ximeng Sun - GenAI @ AMD
Hello, I am a research scientist at AMD GenAI Team. I am interested in the deep learning and computer vision. In particular, I work on efficient learning, vision-language models, and multi-task learning.

I earned my Ph.D. degree from Computer Science at Boston University starting from 2019 Spring, supervised by Prof. Kate Saenko. During my Ph.D. study, I have been fortunate to collaborate with top research labs as an intern, including Meta AI, Google Cloud and IBM Research. During 2022, I was part of Meta AI's team where I had the opportunity to collaborate with Xide Xia, Pengchuan Zhang and Peizhao Zhang. In 2021 Summer, I joined Google Cloud where I worked closely with Clayton Mellina, Xiao Bian and Kihyuk Sohn. In 2019 and 2020 Summer, I worked alongside Rogerio Feris and Rameswar Panda at IBM Research.

Previously, I received my M.S. in ECE from University of Michigan, Ann Arbor and received B.ENG. in Communication Engineering from Beijing University of Posts and Telecommunications.

Ximeng Sun

Publications

Conferences

  • Reuben Tan, Ximeng Sun , Ping Hu, Jui-hsien Wang, Hanieh Deilamsalehy, Bryan A. Plummer, Bryan Russell, Kate Saenko "Koala: Key frame-conditioned long video-LLM". CVPR 2024

    • pdf / code

  • Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Naigang Wang, Bowen Pan, Aude Oliva, Rogerio Feris, Kate Saenko, "All at Once Network Quantization via Collaborative Knowledge Transfer", WACV 2024

    • pdf / code

  • Ximeng Sun, Pengchuan Zhang, Peizhao Zhang, Hardik Shah, Kate Saenko, Xide Xia. "DIME-FM: DIstilling Multimodal and Efficient Foundation Models". ICCV 2023.

    • pdf / code

  • Ximeng Sun, Ping Hu, Kate Saenko. "DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations". NeurIPS 2022.

    • pdf / code

  • Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Aude Oliva, Rogerio Feris, Kate Saenko. "Dynamic Network Quantization for Efficient Video Inference". ICCV 2021.

    • pdf / code

  • Rameswar Panda, Chun-Fu Chen, Quanfu Fan, Ximeng Sun, Kate Saenko, Aude Oliva, Rogerio Feris. "AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition". International Conference on Computer Vision (ICCV), 2021.

    • paper / code

  • Ximeng Sun, Rameswar Panda, Rogerio Feris, Kate Saenko. "AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning". NeurIPS 2020.

    • pdf / code

  • Ximeng Sun, Huijuan Xu, Kate Saenko. "TwoStreamVAN: Improving Motion Modeling in Video Generation". WACV 2020.

    • paper / code

  • Xingchao Peng, Zijun Huang, Ximeng Sun, Kate Saenko. "Domain Agnostic Learning with Disentangled Representations". International Conference on Machine Learning (ICML), 2019.

    • paper / code

  • Ximeng Sun, Ryan Szeto, Jason Corso. "A Temporally-Aware Interpolation Network for Video Frame Inpainting". ACCV 2018.

    • paper / demo / code

Journal

  • Ping Hu, Ximeng Sun, Stan Sclaroff, Kate Saenko. "DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations", TPAMI 2024

    • paper / code

  • Ryan Szeto, Ximeng Sun, Kunyi Lu, Jason Corso. "A Temporally-Aware Interpolation Network for Video Frame Inpainting". TPAMI 2019

    • paper / code

Patents

  • Rameswar Panda, Ximeng Sun, Richard Chen, Rogerio Schmidt Feris and Ekaterina Saenko. "Dynamic network quantization for efficient video inference". US Patent App. 17/566,782

Preprints

  • Piotr Teterwak, Ximeng Sun, Bryan A. Plummer, Kate Saenko, and Ser-Nam Lim. "CLAMP: Contrastive LAnguage Model Prompt-tuning"
  • Ximeng Sun, Kihyuk Sohn, Kate Saenko, Clayton Mellina, and Xiao Bian. "Label Budget Allocation in Multi-Task Learning"
  • Ping Hu, Ximeng Sun, Kate Saenko, Stan Sclaroff. "Weakly-supervised Compositional Feature Aggregation for Few-shot Recognition"
  • Huijuan Xu, Bingyi Kang, Ximeng Sun, Jiashi Feng, Kate Saenko, Trevor Darrell. "Similarity R-C3D for Few-shot Temporal Activity Detection"

Contact

Ximeng Sun
Email: sxm2357 [AT] gmail [dot] com