activity
20222026
most citedFew-Shot Learning with Visual Distribution Calibration and Cross-Modal Distribution Alignment

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Rethinking Position Embedding as a Context Controller for Multi-Reference and Multi-Shot Video Generation

Binyuan Huang, Yuning Lu, Weinan Jia +3

Recent proprietary models such as Sora2 demonstrate promising progress in generating multi-shot videos conditioned on multiple reference characters. However, academic research on t…

cs.CV2025

MoGA: Mixture-of-Groups Attention for End-to-End Long Video Generation

Weinan Jia, Yuning Lu, Mengqi Huang +6

Long video generation with Diffusion Transformers (DiTs) is bottlenecked by the quadratic scaling of full attention with sequence length. Since attention is highly redundant, outpu…

cs.CV2023★ 2 cited

Few-Shot Learning with Visual Distribution Calibration and Cross-Modal Distribution Alignment

Runqi Wang, Hao Zheng, Xiaoyue Duan +5

Pre-trained vision-language models have inspired much research on few-shot learning. However, with only a few training images, there exist two crucial problems: (1) the visual feat…

cs.CV2022

Self-Supervision Can Be a Good Few-Shot Learner

Yuning Lu, Liangjian Wen, Jianzhuang Liu +2

Existing few-shot learning (FSL) methods rely on training with a large labeled dataset, which prevents them from leveraging abundant unlabeled data. From an information-theoretic p…

cs.CV2022

Prompt Distribution Learning

Yuning Lu, Jianzhuang Liu, Yonggang Zhang +2

We present prompt distribution learning for effectively adapting a pre-trained vision-language model to address downstream recognition tasks. Our method not only learns low-bias pr…