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Found 16 papers, 7 papers with code
Learning Object Placement by Inpainting for Compositional Data Augmentation
We study the problem of common sense placement of visual objects in an image.
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity
To support this endeavor, we introduce COMPOSITIONCAP, a new dataset for multi-grained region compositional image captioning, which introduces the task of compositional attribute-aware regional image captioning.
Detecting Human Artifacts from Text-to-Image Models
In this study, we address this challenge by curating Human Artifact Dataset (HAD), the first large-scale dataset specifically designed to identify and localize human artifacts.
Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models
In this work, we conduct a large-scale scientific study into the impact of random seeds during diffusion inference.
Detecting Image Attribution for Text-to-Image Diffusion Models in RGB and Beyond
Modern text-to-image (T2I) diffusion models can generate images with remarkable realism and creativity.
Brush2Prompt: Contextual Prompt Generator for Object Inpainting
Object inpainting is a task that involves adding objects to real images and seamlessly compositing them.
Amodal Completion via Progressive Mixed Context Diffusion
We propose to sidestep many of the difficulties of existing approaches, which typically involve a two-step process of predicting amodal masks and then generating pixels.
Perceptual Artifacts Localization for Image Synthesis Tasks
Recent advancements in deep generative models have facilitated the creation of photo-realistic images across various tasks.
Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications
Egocentric videos offer fine-grained information for high-fidelity modeling of human behaviors.
Inpainting at Modern Camera Resolution by Guided PatchMatch with Auto-Curation
Recently, deep models have established SOTA performance for low-resolution image inpainting, but they lack fidelity at resolutions associated with modern cameras such as 4K or more, and for large holes.
Perceptual Artifacts Localization for Inpainting
Inspired by this workflow, we propose a new learning task of automatic segmentation of inpainting perceptual artifacts, and apply the model for inpainting model evaluation and iterative refinement.
Nested Scale Editing for Conditional Image Synthesis
We propose an image synthesis approach that provides stratified navigation in the latent code space.
Nested Scale-Editing for Conditional Image Synthesis
We propose an image synthesis approach that provides stratified navigation in the latent code space.
Multimodal Image Outpainting With Regularized Normalized Diversification
In this paper, we study the problem of generating a set ofrealistic and diverse backgrounds when given only a smallforeground region.
Deep Image Blending
In addition, we jointly optimize the proposed Poisson blending loss as well as the style and content loss computed from a deep network, and reconstruct the blending region by iteratively updating the pixels using the L-BFGS solver.
Neural Embedding for Physical Manipulations
In common real-world robotic operations, action and state spaces can be vast and sometimes unknown, and observations are often relatively sparse.
