5 papers
Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models
Jiayi Guo, Linqing Wang, Jiangshan Wang +6
Unified multimodal models (UMMs) integrate visual understanding and generation within a single framework. For text-to-image (T2I) tasks, this unified capability allows UMMs to refi…
Taming Rectified Flow for Inversion and Editing
Jiangshan Wang, Junfu Pu, Zhongang Qi +6
Rectified-flow-based diffusion transformers like FLUX and OpenSora have demonstrated outstanding performance in the field of image and video generation. Despite their robust genera…
ArtCrafter: Text-Image Aligning Style Transfer via Embedding Reframing
Nisha Huang, Kaer Huang, Yifan Pu +5
Recent years have witnessed significant advancements in text-guided style transfer, primarily attributed to innovations in diffusion models. These models excel in conditional guida…
COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing
Jiangshan Wang, Yue Ma, Jiayi Guo +3
Video editing is an emerging task, in which most current methods adopt the pre-trained text-to-image (T2I) diffusion model to edit the source video in a zero-shot manner. Despite e…
GRA: Detecting Oriented Objects through Group-wise Rotating and Attention
Jiangshan Wang, Yifan Pu, Yizeng Han +4
Oriented object detection, an emerging task in recent years, aims to identify and locate objects across varied orientations. This requires the detector to accurately capture the or…