引用:Ramesh A, Pavlov M, Goh G, et al. Zero-shot text-to-image generation[C]//International conference on machine learning. Pmlr, 2021: 8821-8831. 论文链接:[2102.12092] Zero-Shot Text-to-Image Generation (arxiv.org) 代码链接:https://github.com/openai/DALL-E 简介 传统上,文本到图像生成...
Distributed Optimization,分布式训练,采用parameter sharding、PowerSGD(像是一种低秩分解) Sample Generation,生成结果的时候,生成N个image结果,用一个预训练好的contrastive model(其实就是CLIP)判断text和image 匹配分数,选择分数最高的那个,论文中采用N=512 Results 效果很好,同时在MSCOCO上 zero-shot的表现也很好;CU...
Zero-shot text-image generation其实就是给文本生图像的任务,文章中使用的都是FID与IS等图像生成的评估指标。 图像生成评估指标 IS(Inception Score)是什么? FromChatGPT(提示词:图像生成评估指标 Inception Score是什么?) Inception Score(简称IS)是一个用于评估生成对抗网络(GANs)生成图像质量的客观指标。它由Tim ...
Zero-Shot Text-to-Image Generation A. Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, I. Sutskever 2021 CogView: Mastering Text-to-Image Generation via Transformers Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang...
MultiGen: Zero-Shot Image Generation fromMulti-modal Prompts The field of text-to-image generation has witnessed substantial advancements in the preceding years, allowing the generation of high-quality images based s... ZF Wu,L Huang,W Wang,... - European Conference on Computer Vision 被引量:...
相关学科: Zero-Shot Text-to-Image GenerationZero-shot Slot FillingText-to-Image GenerationZero-Shot LearningMulti-label Zero-shot LearningAnaphora ResolutionSlot FillingText-To-SqlKnowledge Base PopulationHawkes Process 学科讨论 暂无讨论内容,你可以发起讨论推荐文献...
Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic - YoadTew/zero-shot-image-to-text
Official code base for paper EZIGen: Enhancing zero-shot subject-driven image generation with precise subject encoding and decoupled guidance - ZichengDuan/EZIGen
Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additional models to extract and inject reference subject features, assuming that the Video Diffusion Model (VDM) alone is insufficient for zero-shot customized ...
Zero-shot talking avatar generation aims at synthesizing natural talking videos from speech and a single portrait image. Previous methods have relied on domain-specific heuristics such as warping-based motion representation and 3D Morphable Models, which limit the naturalness and diversity of ...