Papers Image Morphing
“Image Morphing” 태그가 달린 논문 38편 · 필터 해제
FreeMorph: Tuning-Free Generalized Image Morphing with Diffusion Model
We present FreeMorph, the first tuning-free method for image morphing that accommodates inputs with different semantics or layouts. Unlike existing methods that rely on finetuning pre-trained diffusion models and are lim…
DenoisingImage MorphingAddressing degeneracies in latent interpolation for diffusion models
There is an increasing interest in using image-generating diffusion models for deep data augmentation and image morphing. In this context, it is useful to interpolate between latents produced by inverting a set of input …
Data AugmentationImage MorphingFramer: Interactive Frame Interpolation
We propose Framer for interactive frame interpolation, which targets producing smoothly transitioning frames between two images as per user creativity. Concretely, besides taking the start and end frames as inputs, our a…
Image MorphingVideo GenerationSRIF: Semantic Shape Registration Empowered by Diffusion-based Image Morphing and Flow Estimation
In this paper, we propose SRIF, a novel Semantic shape Registration framework based on diffusion-based Image morphing and Flow estimation. More concretely, given a pair of extrinsically aligned shapes, we first render th…
Image MorphingLASER: Tuning-Free LLM-Driven Attention Control for Efficient Text-conditioned Image-to-Animation
Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, e.g., text-conditioned image editing, allowing us to edit the diverse images that convey highly complex …
Image GenerationImage MorphingLanguage ModellingLarge Language ModelGreedy-DiM: Greedy Algorithms for Unreasonably Effective Face Morphs
Morphing attacks are an emerging threat to state-of-the-art Face Recognition (FR) systems, which aim to create a single image that contains the biometric information of multiple identities. Diffusion Morphs (DiM) are a r…
Face Morphing Attack DetectionFace RecognitionGenerative Adversarial NetworkImage MorphingThe Impact of Print-Scanning in Heterogeneous Morph Evaluation Scenarios
Face morphing attacks pose an increasing threat to face recognition (FR) systems. A morphed photo contains biometric information from two different subjects to take advantage of vulnerabilities in FRs. These systems are …
Face RecognitionImage MorphingMORPHOn mitigating stability-plasticity dilemma in CLIP-guided image morphing via geodesic distillation loss
Large-scale language-vision pre-training models, such as CLIP, have achieved remarkable text-guided image morphing results by leveraging several unconditional generative models. However, existing CLIP-guided image morphi…
Image MorphingDiffMorph: Text-less Image Morphing with Diffusion Models
Text-conditioned image generation models are a prevalent use of AI image synthesis, yet intuitively controlling output guided by an artist remains challenging. Current methods require multiple images and textual prompts …
Image GenerationImage MorphingDiffMorpher: Unleashing the Capability of Diffusion Models for Image Morphing
Diffusion models have achieved remarkable image generation quality surpassing previous generative models. However, a notable limitation of diffusion models, in comparison to GANs, is their difficulty in smoothly interpol…
Image GenerationImage MorphingIMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
We present a diffusion-based image morphing approach with perceptually-uniform sampling (IMPUS) that produces smooth, direct and realistic interpolations given an image pair. The embeddings of two images may lie on disti…
DiversityImage GenerationImage MorphingThree-dimensional Bone Image Synthesis with Generative Adversarial Networks
Medical image processing has been highlighted as an area where deep learning-based models have the greatest potential. However, in the medical field in particular, problems of data availability and privacy are hampering …
AttributeImage GenerationImage MorphingFast-DiM: Towards Fast Diffusion Morphs
Diffusion Morphs (DiM) are a recent state-of-the-art method for creating high quality face morphs; however, they require a high number of network function evaluations (NFE) to create the morphs. We propose a new DiM pipe…
Face Morphing Attack DetectionImage MorphingMORPHVulnerability of 3D Face Recognition Systems to Morphing Attacks
In recent years face recognition systems have been brought to the mainstream due to development in hardware and software. Consistent efforts are being made to make them better and more secure. This has also brought devel…
Face RecognitionImage MorphingMeasure transfer via stochastic slicing and matching
This paper studies iterative schemes for measure transfer and approximation problems, which are defined through a slicing-and-matching procedure. Similar to the sliced Wasserstein distance, these schemes benefit from the…
Image MorphingStyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation
Domain adaptation of GANs is a problem of fine-tuning GAN models pretrained on a large dataset (e.g. StyleGAN) to a specific domain with few samples (e.g. painting faces, sketches, etc.). While there are many methods tha…
Domain AdaptationImage MorphingImage-to-Image TranslationMultiview Regenerative Morphing with Dual Flows
This paper aims to address a new task of image morphing under a multiview setting, which takes two sets of multiview images as the input and generates intermediate renderings that not only exhibit smooth transitions betw…
Image MorphingAre GAN-based Morphs Threatening Face Recognition?
Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such …
Face RecognitionImage MorphingResnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset
This residual network has been a broad domain of research in deep learning. Many complex architectures are based upon residual networks. Residual networks are efficient due to skip connections. This paper highlights the…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+14AugStatic - A Light-Weight Image Augmentation Library
The rapid exponential increase in the data led to an abrupt mix of various data types, leading to a deficiency of helpful information. Creating new data with the existing different types of data are presented in this pap…
ClassificationData AugmentationData VisualizationDetecting Image Manipulation+13