평범한 필기장

https://arxiv.org/abs/2405.00878 SonicDiffusion: Audio-Driven Image Generation and Editing with Pretrained Diffusion ModelsWe are witnessing a revolution in conditional image synthesis with the recent success of large scale text-to-image generation methods. This success also opens up new opportunities in controlling the generation and editing process using multi-modal input. Warxiv.org1. Introdu..

https://arxiv.org/abs/2312.06738 InstructAny2Pix: Flexible Visual Editing via Multimodal Instruction FollowingThe ability to provide fine-grained control for generating and editing visual imagery has profound implications for computer vision and its applications. Previous works have explored extending controllability in two directions: instruction tuning with textarxiv.orghttps://github.com/jack..

https://arxiv.org/abs/2312.07509 PEEKABOO: Interactive Video Generation via Masked-DiffusionModern video generation models like Sora have achieved remarkable success in producing high-quality videos. However, a significant limitation is their inability to offer interactive control to users, a feature that promises to open up unprecedented applicaarxiv.org1. Introduction 본 논문에서는 PEEKABOO를 도입한다. 이..

https://arxiv.org/abs/2304.01186 Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free VideosGenerating text-editable and pose-controllable character videos have an imperious demand in creating various digital human. Nevertheless, this task has been restricted by the absence of a comprehensive dataset featuring paired video-pose captions and the garxiv.org1. Introduction Text-to..

https://arxiv.org/abs/2403.17377 Self-Rectifying Diffusion Sampling with Perturbed-Attention GuidanceRecent studies have demonstrated that diffusion models are capable of generating high-quality samples, but their quality heavily depends on sampling guidance techniques, such as classifier guidance (CG) and classifier-free guidance (CFG). These techniquesarxiv.org1. Introduction Diffusion Model들은..

https://arxiv.org/abs/2112.10741 GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion ModelsDiffusion models have recently been shown to generate high-quality synthetic images, especially when paired with a guidance technique to trade off diversity for fidelity. We explore diffusion models for the problem of text-conditional image synthesis and carxiv.org1. Intro..

https://arxiv.org/abs/2404.09512 Magic Clothing: Controllable Garment-Driven Image SynthesisWe propose Magic Clothing, a latent diffusion model (LDM)-based network architecture for an unexplored garment-driven image synthesis task. Aiming at generating customized characters wearing the target garments with diverse text prompts, the image controllarxiv.org1. Introduction 본 논문의 주 contribution을 요약하..