most citedContrastive Multi-Level Graph Neural Networks for Session-based Recommendation

28 citations · 36 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Rethinking the Spatial Inconsistency in Classifier-Free Diffusion Guidance

Dazhong Shen, Guanglu Song, Zeyue Xue +2

Classifier-Free Guidance (CFG) has been widely used in text-to-image diffusion models, where the CFG scale is introduced to control the strength of text guidance on the whole image…

cs.CV2024

Be-Your-Outpainter: Mastering Video Outpainting through Input-Specific Adaptation

Fu-Yun Wang, Xiaoshi Wu, Zhaoyang Huang +5

Video outpainting is a challenging task, aiming at generating video content outside the viewport of the input video while maintaining inter-frame and intra-frame consistency. Exist…

cs.CV20241 cited

Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling

Xiaoyu Shi, Zhaoyang Huang, Fu-Yun Wang +9

We introduce Motion-I2V, a novel framework for consistent and controllable image-to-video generation (I2V). In contrast to previous methods that directly learn the complicated imag…

cs.IR202328 cited

Contrastive Multi-Level Graph Neural Networks for Session-based Recommendation

Fuyun Wang, Xingyu Gao, Zhenyu Chen +1

Session-based recommendation (SBR) aims to predict the next item at a certain time point based on anonymous user behavior sequences. Existing methods typically model session repres…

cs.CV20237 cited

Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising

Fu-Yun Wang, Wenshuo Chen, Guanglu Song +3

Leveraging large-scale image-text datasets and advancements in diffusion models, text-driven generative models have made remarkable strides in the field of image generation and edi…