10 Papers Accepted at CVPR 2024

The Computer Vision and Pattern Recognition (CVPR) conference is a premier annual computer vision event that covers advances in computer vision, pattern recognition, artificial intelligence (AI), machine learning and more.

Held from 17 – 21 June 2024 at Seattle, Washington, CVPR provides a platform for leading scientists, technologists and industry experts to learn, debate and exchange ideas on the latest developments within the industry.

Congratulations to the following scientists from A*STAR’s Centre for Frontier AI Research (CFAR) on having their papers accepted at CVPR 2024:
  • Prof Ivor Tsang, Director
  • Prof Ong Yew Soon, Chief Artificial Intelligence Scientist
  • Dr Lim Joo Hwee, Principal Scientist
  • Dr Joey Zhou, Principal Scientist
  • Dr Foo Chuan Sheng, Principal Scientist
  • Dr Guo Qing, Senior Scientist
  • Dr Zhu Hongyuan, Scientist
  • Dr Liu Yanzhu, Scientist
  • Dr Mohamed Ragab, Scientist
  • Dr Du Jiawei, Senior Research Engineer

List of accepted papers:

  1. CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection
    Jiayi Zhu, Qing Guo, Felix Juefei-Xu, Yihao Huang, Yang Liu, Geguang Pu
  2. Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving
    Jinlong Li, Baolu Li, Zhengzhong Tu, Xinyu Liu, Qing Guo, Felix Juefei-Xu, Runsheng Xu, Hongkai Yu
  3. Spanning Training Progress: Temporal Dual-Depth Scoring (TDDS) for Enhanced Dataset Pruning
    Xin Zhang, Jiawei Du, Weiying Xie, Yunsong Li, Joey Tianyi Zhou
  4. Robust Distillation via Untargeted and Targeted Intermediate Adversarial Samples
    Junhao Dong, Piotr Koniusz, Junxi Chen, Z. Jane Wang, Yew-Soon Ong
  5. Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners
    Junhao Dong, Piotr Koniusz, Junxi Chen, Xiaohua Xie, Yew-Soon Ong
  6. Diffusion Time-step Curriculum for One Image to 3D Generation
    Yi Xuanyu, Zike Wu, Qingshan Xu, Pan Zhou, Joo Hwee Lim, Hanwang Zhang
  7. LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning
    Sijin Chen, Xin Chen, Chi Zhang, Mingsheng Li, Gang Yu, Hao Fei, Hongyuan Zhu, Jiayuan Fan, Tao Chen
  8. MACE: Mass Concept Erasure in Diffusion Models
    Shilin Lu, Zilan Wang, Leyang Li, Yanzhu Liu, Adams Kong
  9. AHIVE: Anatomy-aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval
    Sixing Yan, William Cheung, Ivor Tsang, Keith Chiu, Terence M. Tong, Ka Chun Cheung, Simon See
  10. Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias
    Wenyu Zhang, Liu Qingmu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo

Find out more about CVPR 2024.