Greetings! I’m currently a PhD student at the University of Science and Technology of China. And I serve as a research intern at Tencent.
My research interest includes:
- semantic segmentation
- parameter-efficient fine-tuning
- vision foundation models
- open-vocabulary detection/segmentation
I sincerely welcome discussions and collaborations. If you’re interested, please feel free to reach out to me via email.
🔥 News
- 2024.09: 🔥 Delighted to announce that Masked Pre-trained Model Enables Universal Zero-shot Denoiser were accepted by NeurIPS 2024!
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2024.02: 🔥 Rein is accepted in CVPR 2024! [Project Page]
- 2024.01: 🔥 Rein achieves SOTA in Cityscapes $\rightarrow$ ACDC test set generalization!
- 2023.10: 🔥 Rein is released and achieves SOTA in domain generalized semantic segmentation!
- 2023.07: 🎉 DTP is accepted in ICCV 2023 and achieves SOTA in night-time and full-time semantic segmentation!
- 2022.10: Our DDB receives the Spotlight Award in NeurIPS 2022!
- 2022.09: DDB is accepted in NeurIPS 2022 and achieves SOTA with ResNet counterparts on the single-source, multi-source, and multi-target domain-adaptive semantic segmentation tasks!
- 2022.03: A discriminator-free adversarial domain adaptation framework DALN is accepted in CVPR 2022!
📝 Publications
(* denotes equal contribution.)
Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation
Zhixiang Wei*, Lin Chen*, Yi Jin*, Xiaoxiao Ma, Tianle Liu, Pengyang Ling, Ben Wang, Huaian Chen, Jinjin Zheng
- We propose the Reins framework, which efficiently fine-tunes vision foundation models for the domain generalized semantic segmentation (DGSS) task with just 1% trainable parameters, surprisingly surpassing full parameter fine-tuning. And Reins builds a new SOTA in various DGSS benchmarks.
Disentangle then Parse: Night-time Semantic Segmentation with Illumination Disentanglement
Zhixiang Wei*, Lin Chen*, Tao Tu, Huaian Chen, Pengyang Ling, Yi Jin
- We propose a novel nigh-time semantic segmentation paradigm, i.e., disentangle then parse (DTP), which explicitly disentangles night-time images into light-invariant reflectance and light-specific illumination components and then recognizes semantics based on their adaptive fusion.
Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation
Lin Chen*, Zhixiang Wei*, Xin Jin*, Huaian Chen, Miao Zheng, Kai Chen, Yi Jin
- We leverage the complementary characteristics of the coarse-wise and fine-wise data mixing techniques to progressively transfer the knowledge from the source to the target domain.
Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation
Lin Chen*, Huaian Chen*, Zhixiang Wei, Xin Jin, Xiao Tan, Yi Jin, Enhong Chen
- We reuse the category classifier as a discriminator to form a discriminator-free adversarial learning framework.
NeurIPS 2024Masked Pre-trained Model Enables Universal Zero-shot Denoiser, Xiaoxiao Ma, Zhixiang Wei*, et al.
🎖 Honors and Awards
- 2023.10 National Scholarship Award(Top 1%)
- 2021~2023 The First Prize Scholarship of USTC for three consecutive years
- 2021.05 Outstanding Graduates of Anhui Province
📝 Academic Service (Reviewer)
- IEEE TPAMI
- IEEE TNNLS
💬 Invited Talks
- 2024.09 IEEE ITSC Workshop: Foundation Models for Autonomous Driving, in Canada