Papers Conditional Image Generation
“Conditional Image Generation” 태그가 달린 논문 327편 · 필터 해제
Exploring Intra-Class Variation Factors With Learnable Cluster Prompts for Semi-Supervised Image Synthesis
Semi-supervised class-conditional image synthesis is typically performed by inferring and injecting class labels into a conditional Generative Adversarial Network (GAN). The supervision in the form of class identity …
Conditional Image GenerationGenerative Adversarial NetworkImage GenerationNeural Characteristic Function Learning for Conditional Image Generation
The emergence of conditional generative adversarial networks (cGANs) has revolutionised the way we approach and control the generation, by means of adversarially learning joint distributions of data and auxiliary inf…
Conditional Image GenerationGenerative Adversarial NetworkImage GenerationForeground-Background Separation through Concept Distillation from Generative Image Foundation Models
Curating datasets for object segmentation is a difficult task. With the advent of large-scale pre-trained generative models, conditional image generation has been given a significant boost in result quality and ease …
Conditional Image GenerationImage GenerationMedical Image AnalysisObject+2Zero-Shot Object Segmentation through Concept Distillation from Generative Image Foundation Models
Curating datasets for object segmentation is a difficult task. With the advent of large-scale pre-trained generative models, conditional image generation has been given a significant boost in result quality and ease of u…
Conditional Image GenerationImage GenerationObjectSegmentation+1Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis
Vector-Quantized (VQ-based) generative models usually consist of two basic components, i.e., VQ tokenizers and generative transformers. Prior research focuses on improving the reconstruction fidelity of VQ tokenizers but…
Conditional Image GenerationDecoderImage GenerationSemantic CompressionRefining Generative Process with Discriminator Guidance in Score-based Diffusion Models
The proposed method, Discriminator Guidance, aims to improve sample generation of pre-trained diffusion models. The approach introduces a discriminator that gives explicit supervision to a denoising sample path whether i…
Conditional Image GenerationDenoisingImage GenerationA survey on knowledge-enhanced multimodal learning
Multimodal learning has been a field of increasing interest, aiming to combine various modalities in a single joint representation. Especially in the area of visiolinguistic (VL) learning multiple models and techniques h…
Conditional Image GenerationFactual Visual Question AnsweringFairnessImage Captioning+13A Novel Sampling Scheme for Text- and Image-Conditional Image Synthesis in Quantized Latent Spaces
Recent advancements in the domain of text-to-image synthesis have culminated in a multitude of enhancements pertaining to quality, fidelity, and diversity. Contemporary techniques enable the generation of highly intricat…
Conditional Image GenerationDenoisingDiversityImage Generation+2Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation
Based on the Denoising Diffusion Probabilistic Model (DDPM), medical image segmentation can be described as a conditional image generation task, which allows to compute pixel-wise uncertainty maps of the segmentation and…
Conditional Image GenerationDenoisingImage GenerationImage Segmentation+3Discrete Predictor-Corrector Diffusion Models for Image Synthesis
We introduce Discrete Predictor-Corrector diffusion models (DPC), extending predictor-corrector samplers in Gaussian diffusion models to the discrete case. Predictor-corrector samplers are a class of samplers for diffusi…
Conditional Image GenerationImage GenerationAll are Worth Words: A ViT Backbone for Diffusion Models
Vision transformers (ViT) have shown promise in various vision tasks while the U-Net based on a convolutional neural network (CNN) remains dominant in diffusion models. We design a simple and general ViT-based architectu…
AllConditional Image GenerationImage GenerationText to Image Generation+1Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Diffusion models (DMs) have shown great potential for high-quality image synthesis. However, when it comes to producing images with complex scenes, how to properly describe both image global structures and object details…
Conditional Image GenerationDenoisingImage GenerationRepresentation LearningImproving GANs for Long-Tailed Data through Group Spectral Regularization
Deep long-tailed learning aims to train useful deep networks on practical, real-world imbalanced distributions, wherein most labels of the tail classes are associated with a few samples. There has been a large body of wo…
Conditional Image GenerationImage GenerationGenerator Knows What Discriminator Should Learn in Unconditional GANs
Recent methods for conditional image generation benefit from dense supervision such as segmentation label maps to achieve high-fidelity. However, it is rarely explored to employ dense supervision for unconditional image …
Conditional Image GenerationImage GenerationUnconditional Image GenerationAuto-regressive Image Synthesis with Integrated Quantization
Deep generative models have achieved conspicuous progress in realistic image synthesis with multifarious conditional inputs, while generating diverse yet high-fidelity images remains a grand challenge in conditional imag…
Conditional Image GenerationImage GenerationInductive BiasQuantizationEntropy-driven Sampling and Training Scheme for Conditional Diffusion Generation
Denoising Diffusion Probabilistic Model (DDPM) is able to make flexible conditional image generation from prior noise to real data, by introducing an independent noise-aware classifier to provide conditional gradient gui…
Conditional Image GenerationDenoisingImage GenerationThe ArtBench Dataset: Benchmarking Generative Models with Artworks
We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation. It comprises 60,000 images of artwork from 10 distinctive artistic styles…
BenchmarkingConditional Image GenerationImage GenerationUnconditional Image GenerationDraft-and-Revise: Effective Image Generation with Contextual RQ-Transformer
Although autoregressive models have achieved promising results on image generation, their unidirectional generation process prevents the resultant images from fully reflecting global contexts. To address the issue, we pr…
Conditional Image GenerationImage GenerationText-to-Image GenerationPAGER: Progressive Attribute-Guided Extendable Robust Image Generation
This work presents a generative modeling approach based on successive subspace learning (SSL). Unlike most generative models in the literature, our method does not utilize neural networks to analyze the underlying source…
AttributeConditional Image GenerationImage GenerationUnconditional Image GenerationOn Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
Conditional image generation has paved the way for several breakthroughs in image editing, generating stock photos and 3-D object generation. This continues to be a significant area of interest with the rise of new state…
Conditional Image GenerationDiversityImage Generation