6 papers · 1 filter
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…
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…
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…
FINE: Factorizing Knowledge for Initialization of Variable-sized Diffusion Models
Yucheng Xie, Fu Feng, Ruixiao Shi +4
The training of diffusion models is computationally intensive, making effective pre-training essential. However, real-world deployments often demand models of variable sizes due to…
KIND: Knowledge Integration and Diversion for Training Decomposable Models
Yucheng Xie, Fu Feng, Ruixiao Shi +3
Pre-trained models have become the preferred backbone due to the increasing complexity of model parameters. However, traditional pre-trained models often face deployment challenges…