53 citations · 85 across the 7 of their papers we have counts for
7 papers
The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generation
Chenyu Mu, Xin He, Qu Yang +13
Recent advances in video generation have produced models capable of synthesizing stunning visual content from simple text prompts. However, these models struggle to generate long-f…
Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels
Chenyu Mu, Guihai Chen, Xun Yang +2
Medical image segmentation is crucial for clinical applications, but it is frequently disrupted by noisy annotations and ambiguous anatomical boundaries, limiting its application i…
MSR: Making Self-supervised learning Robust to Aggressive Augmentations
Yingbin Bai, Erkun Yang, Zhaoqing Wang +5
Most recent self-supervised learning methods learn visual representation by contrasting different augmented views of images. Compared with supervised learning, more aggressive augm…
Understanding and Improving Early Stopping for Learning with Noisy Labels
Yingbin Bai, Erkun Yang, Bo Han +5
The memorization effect of deep neural network (DNN) plays a pivotal role in many state-of-the-art label-noise learning methods. To exploit this property, the early stopping trick,…
Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network
Shuo Yang, Erkun Yang, Bo Han +4
In label-noise learning, estimating the transition matrix is a hot topic as the matrix plays an important role in building statistically consistent classifiers. Traditionally, the…
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs
Erkun Yang, Tongliang Liu, Cheng Deng +2
Due to the high storage and search efficiency, hashing has become prevalent for large-scale similarity search. Particularly, deep hashing methods have greatly improved the search p…
Shared Predictive Cross-Modal Deep Quantization
Erkun Yang, Cheng Deng, Chao Li +3
With explosive growth of data volume and ever-increasing diversity of data modalities, cross-modal similarity search, which conducts nearest neighbor search across different modali…