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20192026
most citedSample Selection with Uncertainty of Losses for Learning with Noisy Labels

49 citations · 111 across the 14 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

Omnimodal Dataset Distillation via High-order Proxy Alignment

Yuxuan Gao, Xiaohao Liu, Xiaobo Xia +1

Dataset distillation compresses large-scale datasets into compact synthetic sets while preserving training performance, but existing methods are largely restricted to single-modal…

cs.CV2024

LaVin-DiT: Large Vision Diffusion Transformer

Zhaoqing Wang, Xiaobo Xia, Runnan Chen +4

This paper presents the Large Vision Diffusion Transformer (LaVin-DiT), a scalable and unified foundation model designed to tackle over 20 computer vision tasks in a generative fra…

cs.CV2024

DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception

Run Luo, Yunshui Li, Longze Chen +9

The development of large language models (LLMs) has significantly advanced the emergence of large multimodal models (LMMs). While LMMs have achieved tremendous success by promoting…

cs.CV2024

Few-Shot Adversarial Prompt Learning on Vision-Language Models

Yiwei Zhou, Xiaobo Xia, Zhiwei Lin +2

The vulnerability of deep neural networks to imperceptible adversarial perturbations has attracted widespread attention. Inspired by the success of vision-language foundation model…

cs.CV2024

Open-Vocabulary Segmentation with Unpaired Mask-Text Supervision

Zhaoqing Wang, Xiaobo Xia, Ziye Chen +4

Current state-of-the-art open-vocabulary segmentation methods typically rely on image-mask-text triplet annotations for supervision. However, acquiring such detailed annotations is…

cs.CV20231 cited

Robust Generalization against Photon-Limited Corruptions via Worst-Case Sharpness Minimization

Zhuo Huang, Miaoxi Zhu, Xiaobo Xia +6

Robust generalization aims to tackle the most challenging data distributions which are rare in the training set and contain severe noises, i.e., photon-limited corruptions. Common…