Conditional Image Generation
133 papers with code • 10 benchmarks • 8 datasets
Conditional image generation is the task of generating new images from a dataset conditional on their class.
( Image credit: PixelCNN++ )
Benchmarks
These leaderboards are used to track progress in Conditional Image Generation
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Libraries
Use these libraries to find Conditional Image Generation models and implementationsDatasets
CIFAR-10
MS COCO
CIFAR-100
Tiny ImageNet
ImageNet-LT
ArtBench-10 (32x32)
Latest papers
Benchmarking Counterfactual Image Generation
gulnazaki/counterfactual-benchmark
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Counterfactual image generation is pivotal for understanding the causal relations of variables, with applications in interpretability and generation of unbiased synthetic data.
CLIP-VQDiffusion : Langauge Free Training of Text To Image generation using CLIP and vector quantized diffusion model
infiniq-ai1/clipvqdiffusion
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There has been a significant progress in text conditional image generation models.
FineDiffusion: Scaling up Diffusion Models for Fine-grained Image Generation with 10,000 Classes
FineDiffusion/FineDiffusion
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The class-conditional image generation based on diffusion models is renowned for generating high-quality and diverse images.
Scalable Diffusion Models with State Space Backbone
feizc/dis
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We endeavor to train diffusion models for image data, wherein the traditional U-Net backbone is supplanted by a state space backbone, functioning on raw patches or latent space.
AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning
g-u-n/animatelcm
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We validate the proposed strategy in image-conditioned video generation and layout-conditioned video generation, all achieving top-performing results.
Return of Unconditional Generation: A Self-supervised Representation Generation Method
LTH14/rcg
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This gap can be attributed to the lack of semantic information provided by labels.
GIVT: Generative Infinite-Vocabulary Transformers
google-research/big_vision
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We introduce generative infinite-vocabulary transformers (GIVT) which generate vector sequences with real-valued entries, instead of discrete tokens from a finite vocabulary.
Tell2Design: A Dataset for Language-Guided Floor Plan Generation
We make multiple contributions to initiate research on this task.
Enhancing Object Coherence in Layout-to-Image Synthesis
Layout-to-image synthesis is an emerging technique in conditional image generation.
Particle 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.
