평범한 필기장

Paper : https://arxiv.org/abs/2304.08465 MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and EditingDespite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results. For example, generation approaches usually fail to synthesize multiple imaarxiv.o..

Paper : https://arxiv.org/abs/2310.01506 Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of CodeText-guided diffusion models have revolutionized image generation and editing, offering exceptional realism and diversity. Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt, the process comarxiv.orgProject Page : https:..

Paper : https://arxiv.org/abs/2401.11739 EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion ModelsDiffusion models have recently received increasing research attention for their remarkable transfer abilities in semantic segmentation tasks. However, generating fine-grained segmentation masks with diffusion models often requires additional training on anarxiv.org0. Abstract Diffusion m..

Paper : https://arxiv.org/abs/2303.04761 Video-P2P: Video Editing with Cross-attention ControlThis paper presents Video-P2P, a novel framework for real-world video editing with cross-attention control. While attention control has proven effective for image editing with pre-trained image generation models, there are currently no large-scale video gearxiv.orgGithub : https://github.com/dvlab-resea..