Papers Conditional Image Generation
“Conditional Image Generation” 태그가 달린 논문 327편 · 필터 해제
AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data
This paper introduces an effective method for computation-efficient personalized style video generation without requiring access to any personalized video data. It reduces the necessary generation time of similarly sized…
Conditional Image GenerationDenoisingImage GenerationMotion Generation+1Diffusion Model Compression for Image-to-Image Translation
As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive resu…
Conditional Image GenerationDenoisingImage GenerationImage Restoration+4UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion
Existing text-to-image diffusion models primarily generate images from text prompts. However, the inherent conciseness of textual descriptions poses challenges in faithfully synthesizing images with intricate details, su…
Conditional Image GenerationDenoisingImage GenerationImage Segmentation+6CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data
Content creation and image editing can benefit from flexible user controls. A common intermediate representation for conditional image generation is a semantic map, that has information of objects present in the image. W…
Conditional Image GenerationImage GenerationImage ManipulationImage-to-Image TranslationVIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation
In the rapidly advancing field of conditional image generation research, challenges such as limited explainability lie in effectively evaluating the performance and capabilities of various models. This paper introduces V…
Conditional Image GenerationGeneral KnowledgeImage GenerationConditional Image Generation with Pretrained Generative Model
In recent years, diffusion models have gained popularity for their ability to generate higher-quality images in comparison to GAN models. However, like any other large generative models, these models require a huge amoun…
Conditional Image GenerationImage GenerationmodelUnlocking Pre-trained Image Backbones for Semantic Image Synthesis
Semantic image synthesis, i.e., generating images from user-provided semantic label maps, is an important conditional image generation task as it allows to control both the content as well as the spatial layout of genera…
Conditional Image Generationimage-classificationImage ClassificationImage Generation+1ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation
Due to advancements in infrastructural modulations, architectural design is one of the most peculiar and tedious processes. As the technology evolves to the next phase, using some latest techniques like generative advers…
3D Architecture3D Depth Estimation3D Semantic Scene Completion from a single 2D image3D Shape Modeling+6Return of Unconditional Generation: A Self-supervised Representation Generation Method
Unconditional generation -- the problem of modeling data distribution without relying on human-annotated labels -- is a long-standing and fundamental challenge in generative models, creating a potential of learning from …
Conditional Image GenerationImage GenerationUnconditional Image GenerationGIVT: Generative Infinite-Vocabulary Transformers
We introduce Generative Infinite-Vocabulary Transformers (GIVT) which generate vector sequences with real-valued entries, instead of discrete tokens from a finite vocabulary. To this end, we propose two surprisingly simp…
Conditional Image GenerationDecoderDepth EstimationImage Generation+1Manifold Preserving Guided Diffusion
Despite the recent advancements, conditional image generation still faces challenges of cost, generalizability, and the need for task-specific training. In this paper, we propose Manifold Preserving Guided Diffusion (MPG…
Conditional Image GenerationImage GenerationTell2Design: A Dataset for Language-Guided Floor Plan Generation
We consider the task of generating designs directly from natural language descriptions, and consider floor plan generation as the initial research area. Language conditional generative models have recently been very succ…
Conditional Image GenerationImage GenerationGuided Flows for Generative Modeling and Decision Making
Classifier-free guidance is a key component for enhancing the performance of conditional generative models across diverse tasks. While it has previously demonstrated remarkable improvements for the sample quality, it has…
Conditional Image GenerationDecision MakingImage Generationreinforcement-learning+4Enhancing Object Coherence in Layout-to-Image Synthesis
Layout-to-image synthesis is an emerging technique in conditional image generation. It aims to generate complex scenes, where users require fine control over the layout of the objects in a scene. However, it remains chal…
Conditional Image GenerationImage GenerationObjectTexture SynthesisParticle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
In light of the widespread success of generative models, a significant amount of research has gone into speeding up their sampling time. However, generative models are often sampled multiple times to obtain a diverse set…
Conditional Image GenerationDiversityImage GenerationElucidating The Design Space of Classifier-Guided Diffusion Generation
Guidance in conditional diffusion generation is of great importance for sample quality and controllability. However, existing guidance schemes are to be desired. On one hand, mainstream methods such as classifier guidanc…
Conditional Image GenerationImage GenerationText to Image GenerationText-to-Image GenerationPosterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
We propose conditional flows of the maximum mean discrepancy (MMD) with the negative distance kernel for posterior sampling and conditional generative modeling. This MMD, which is also known as energy distance, has sever…
Conditional Image GenerationImage GenerationImagenHub: Standardizing the evaluation of conditional image generation models
Recently, a myriad of conditional image generation and editing models have been developed to serve different downstream tasks, including text-to-image generation, text-guided image editing, subject-driven image generatio…
Conditional Image GenerationImage Generationtext-guided-image-editingText to Image Generation+1Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis
Conditional generative models typically demand large annotated training sets to achieve high-quality synthesis. As a result, there has been significant interest in designing models that perform plug-and-play generation, …
ColorizationConditional Image GenerationImage GenerationImage Super-Resolution+2Diverse Semantic Image Editing with Style Codes
Semantic image editing requires inpainting pixels following a semantic map. It is a challenging task since this inpainting requires both harmony with the context and strict compliance with the semantic maps. The majority…
Conditional Image GenerationImage Generation