most citedBinding-Adaptive Diffusion Models for Structure-Based Drug Design

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Efficient Event Stream Super-Resolution with Recursive Multi-Branch Fusion

Quanmin Liang, Zhilin Huang, Xiawu Zheng +4

Current Event Stream Super-Resolution (ESR) methods overlook the redundant and complementary information present in positive and negative events within the event stream, employing…

cs.CV2024

Bilateral Event Mining and Complementary for Event Stream Super-Resolution

Zhilin Huang, Quanmin Liang, Yijie Yu +5

Event Stream Super-Resolution (ESR) aims to address the challenge of insufficient spatial resolution in event streams, which holds great significance for the application of event c…

cs.CV2024

Motion-aware Latent Diffusion Models for Video Frame Interpolation

Zhilin Huang, Yijie Yu, Ling Yang +6

With the advancement of AIGC, video frame interpolation (VFI) has become a crucial component in existing video generation frameworks, attracting widespread research interest. For t…

q-bio.BM20242 cited

Binding-Adaptive Diffusion Models for Structure-Based Drug Design

Zhilin Huang, Ling Yang, Zaixi Zhang +6

Structure-based drug design (SBDD) aims to generate 3D ligand molecules that bind to specific protein targets. Existing 3D deep generative models including diffusion models have sh…

cs.CV2024

Improving Diffusion-Based Image Synthesis with Context Prediction

Ling Yang, Jingwei Liu, Shenda Hong +5

Diffusion models are a new class of generative models, and have dramatically promoted image generation with unprecedented quality and diversity. Existing diffusion models mainly tr…