activity
20222025
most citedReusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation

13 citations · 14 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Rein++: Efficient Generalization and Adaptation for Semantic Segmentation with Vision Foundation Models

Zhixiang Wei, Xiaoxiao Ma, Ruishen Yan +5

Vision Foundation Models(VFMs) have achieved remarkable success in various computer vision tasks. However, their application to semantic segmentation is hindered by two significant…

cs.CV2024

Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement

Yuxuan Gu, Yi Jin, Ben Wang +6

In this work, we observe that the generators, which are pre-trained on massive natural images, inherently hold the promising potential for superior low-light image enhancement agai…

cs.CV2024★ 1 cited

Masked Pre-training Enables Universal Zero-shot Denoiser

Xiaoxiao Ma, Zhixiang Wei, Yi Jin +5

In this work, we observe that model trained on vast general images via masking strategy, has been naturally embedded with their distribution knowledge, thus spontaneously attains t…

cs.CL2022

Non-Parametric Domain Adaptation for End-to-End Speech Translation

Yichao Du, Weizhi Wang, Zhirui Zhang +4

End-to-End Speech Translation (E2E-ST) has received increasing attention due to the potential of its less error propagation, lower latency, and fewer parameters. However, the effec…

cs.CV2022★ 13 cited

Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation

Lin Chen, Huaian Chen, Zhixiang Wei +4

Adversarial learning has achieved remarkable performances for unsupervised domain adaptation (UDA). Existing adversarial UDA methods typically adopt an additional discriminator to…