7 papers
Self-Supervised Weight Templates for Scalable Vision Model Initialization
Yucheng Xie, Fu Feng, Ruixiao Shi +3
The increasing scale and complexity of modern model parameters underscore the importance of pre-trained models. However, deployment often demands architectures of varying sizes, ex…
Towards Understanding Feature Learning in Parameter Transfer
Hua Yuan, Xuran Meng, Qiufeng Wang +6
Parameter transfer is a central paradigm in transfer learning, enabling knowledge reuse across tasks and domains by sharing model parameters between upstream and downstream models.…
REFINE-CONTROL: A Semi-supervised Distillation Method For Conditional Image Generation
Yicheng Jiang, Jin Yuan, Hua Yuan +2
Conditional image generation models have achieved remarkable results by leveraging text-based control to generate customized images. However, the high resource demands of these mod…
Enriching Knowledge Distillation with Intra-Class Contrastive Learning
Hua Yuan, Ning Xu, Xin Geng +1
Since the advent of knowledge distillation, much research has focused on how the soft labels generated by the teacher model can be utilized effectively. Existing studies points out…
Mask Consistency Regularization in Object Removal
Hua Yuan, Jin Yuan, Yicheng Jiang +3
Object removal, a challenging task within image inpainting, involves seamlessly filling the removed region with content that matches the surrounding context. Despite advancements i…
DivControl: Knowledge Diversion for Controllable Image Generation
Yucheng Xie, Fu Feng, Ruixiao Shi +3
Diffusion models have advanced from text-to-image (T2I) to image-to-image (I2I) generation by incorporating structured inputs such as depth maps, enabling fine-grained spatial cont…