12 citations · 20 across the 8 of their papers we have counts for
8 papers
DreamVAR: Taming Reinforced Visual Autoregressive Model for High-Fidelity Subject-Driven Image Generation
Xin Jiang, Jingwen Chen, Yehao Li +5
Recent advances in subject-driven image generation using diffusion models have attracted considerable attention for their remarkable capabilities in producing high-quality images.…
Incorporating Visual Correspondence into Diffusion Model for Virtual Try-On
Siqi Wan, Jingwen Chen, Yingwei Pan +2
Diffusion models have shown preliminary success in virtual try-on (VTON) task. The typical dual-branch architecture comprises two UNets for implicit garment deformation and synthes…
Unleashing Text-to-Image Diffusion Prior for Zero-Shot Image Captioning
Jianjie Luo, Jingwen Chen, Yehao Li +4
Recently, zero-shot image captioning has gained increasing attention, where only text data is available for training. The remarkable progress in text-to-image diffusion model prese…
Improving Text-guided Object Inpainting with Semantic Pre-inpainting
Yifu Chen, Jingwen Chen, Yingwei Pan +4
Recent years have witnessed the success of large text-to-image diffusion models and their remarkable potential to generate high-quality images. The further pursuit of enhancing the…
Improving Virtual Try-On with Garment-focused Diffusion Models
Siqi Wan, Yehao Li, Jingwen Chen +4
Diffusion models have led to the revolutionizing of generative modeling in numerous image synthesis tasks. Nevertheless, it is not trivial to directly apply diffusion models for sy…
ControlStyle: Text-Driven Stylized Image Generation Using Diffusion Priors
Jingwen Chen, Yingwei Pan, Ting Yao +1
Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text…
Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network
Yehao Li, Yingwei Pan, Ting Yao +2
Despite having impressive vision-language (VL) pretraining with BERT-based encoder for VL understanding, the pretraining of a universal encoder-decoder for both VL understanding an…
Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning
Jingwen Chen, Yingwei Pan, Yehao Li +3
It is well believed that video captioning is a fundamental but challenging task in both computer vision and artificial intelligence fields. The prevalent approach is to map an inpu…