7 citations · 15 across the 10 of their papers we have counts for
5 papers · 1 filter
Coherent Video Inpainting Using Optical Flow-Guided Efficient Diffusion
Bohai Gu, Hao Luo, Song Guo +2
The text-guided video inpainting technique has significantly improved the performance of content generation applications. A recent family for these improvements uses diffusion mode…
ParsNets: A Parsimonious Orthogonal and Low-Rank Linear Networks for Zero-Shot Learning
Jingcai Guo, Qihua Zhou, Ruibing Li +5
This paper provides a novel parsimonious yet efficient design for zero-shot learning (ZSL), dubbed ParsNets, where we are interested in learning a composition of on-device friendly…
Attribute-Aware Representation Rectification for Generalized Zero-Shot Learning
Zhijie Rao, Jingcai Guo, Xiaocheng Lu +5
Generalized Zero-shot Learning (GZSL) has yielded remarkable performance by designing a series of unbiased visual-semantics mappings, wherein, the precision relies heavily on the c…
FreePIH: Training-Free Painterly Image Harmonization with Diffusion Model
Ruibin Li, Jingcai Guo, Song Guo +2
This paper provides an efficient training-free painterly image harmonization (PIH) method, dubbed FreePIH, that leverages only a pre-trained diffusion model to achieve state-of-the…
Dissecting Arbitrary-scale Super-resolution Capability from Pre-trained Diffusion Generative Models
Ruibin Li, Qihua Zhou, Song Guo +5
Diffusion-based Generative Models (DGMs) have achieved unparalleled performance in synthesizing high-quality visual content, opening up the opportunity to improve image super-resol…