2 citations · 3 across the 5 of their papers we have counts for
5 papers
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
Let's Roll a BiFTA: Bi-refinement for Fine-grained Text-visual Alignment in Vision-Language Models
Yuhao Sun, Chengyi Cai, Jiacheng Zhang +3
Recent research has shown that aligning fine-grained text descriptions with localized image patches can significantly improve the zero-shot performance of pre-trained vision-langua…
SGIA: Enhancing Fine-Grained Visual Classification with Sequence Generative Image Augmentation
Qiyu Liao, Xin Yuan, Min Xu +1
In Fine-Grained Visual Classification (FGVC), distinguishing highly similar subcategories remains a formidable challenge, often necessitating datasets with extensive variability. T…
Enhancing User-Centric Privacy Protection: An Interactive Framework through Diffusion Models and Machine Unlearning
Huaxi Huang, Xin Yuan, Qiyu Liao +2
In the realm of multimedia data analysis, the extensive use of image datasets has escalated concerns over privacy protection within such data. Current research predominantly focuse…
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution
Xin Yuan, Jinoo Baek, Keyang Xu +2
We propose an efficient diffusion-based text-to-video super-resolution (SR) tuning approach that leverages the readily learned capacity of pixel level image diffusion model to capt…