paper-with-me

Papers Facial Editing

“Facial Editing” 태그가 달린 논문 29편 · 필터 해제

SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Models

2025-05-31 · Yule Zhu, Ping Liu, Zhedong Zheng, Wei Liu

Diffusion models have recently enabled precise and photorealistic facial editing across a wide range of semantic attributes. Beyond single-step modifications, a growing class of applications now demands the ability to an…

AttributeFacial Editing

DynamicID: Zero-Shot Multi-ID Image Personalization with Flexible Facial Editability

2025-03-09 · Xirui Hu, Jiahao Wang, Hao Chen, Weizhan Zhang 외

Recent advancements in text-to-image generation have spurred interest in personalized human image generation, which aims to create novel images featuring specific human identities as reference images indicate. Although e…

Contrastive LearningFacial EditingImage GenerationText to Image Generation+1

Towards Fair and Robust Face Parsing for Generative AI: A Multi-Objective Approach

2025-02-06 · Sophia J. Abraham, Jonathan D. Hauenstein, Walter J. Scheirer

Face parsing is a fundamental task in computer vision, enabling applications such as identity verification, facial editing, and controllable image synthesis. However, existing face parsing models often lack fairness and …

Face GenerationFace ParsingFacial EditingFairness+2

FACEMUG: A Multimodal Generative and Fusion Framework for Local Facial Editing

2024-12-26 · Wanglong Lu, Jikai Wang, Xiaogang Jin, Xianta Jiang 외

Existing facial editing methods have achieved remarkable results, yet they often fall short in supporting multimodal conditional local facial editing. One of the significant evidences is that their output image quality d…

AttributeFacial Editing

Editable-DeepSC: Reliable Cross-Modal Semantic Communications for Facial Editing

2024-11-24 · Bin Chen, Wenbo Yu, Qinshan Zhang, Tianqu Zhuang 외

Real-time computer vision (CV) plays a crucial role in various real-world applications, whose performance is highly dependent on communication networks. Nonetheless, the data-oriented characteristics of conventional comm…

Facial EditingSemantic Communication

SegTalker: Segmentation-based Talking Face Generation with Mask-guided Local Editing

2024-09-05 · Lingyu Xiong, Xize Cheng, Jintao Tan, Xianjia Wu 외

Audio-driven talking face generation aims to synthesize video with lip movements synchronized to input audio. However, current generative techniques face challenges in preserving intricate regional textures (skin, teeth)…

Face GenerationFacial EditingSegmentationTalking Face Generation

Mitigating the Impact of Attribute Editing on Face Recognition

2024-03-12 · Sudipta Banerjee, Sai Pranaswi Mullangi, Shruti Wagle, Chinmay Hegde 외

Through a large-scale study over diverse face images, we show that facial attribute editing using modern generative AI models can severely degrade automated face recognition systems. This degradation persists even with i…

AttributeFace RecognitionFacial EditingQuestion Answering+2

3D-Aware Face Editing via Warping-Guided Latent Direction Learning

2024-01-01 · CVPR 2024 1 · Yuhao Cheng, Zhuo Chen, Xingyu Ren, Wenhan Zhu 외

3D facial editing a longstanding task in computer vision with broad applications is expected to fast and intuitively manipulate any face from arbitrary viewpoints following the user's will. Existing works have limita…

AttributeFacial Editing

A Generalist FaceX via Learning Unified Facial Representation

2023-12-31 · Yue Han, Jiangning Zhang, Junwei Zhu, Xiangtai Li 외

This work presents FaceX framework, a novel facial generalist model capable of handling diverse facial tasks simultaneously. To achieve this goal, we initially formulate a unified facial representation for a broad spectr…

Facial Editing

E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion

2023-10-23 · Maomao Li, Ge Yuan, Cairong Wang, Zhian Liu 외

This paper proposes a novel approach to face swapping from the perspective of fine-grained facial editing, dubbed "editing for swapping" (E4S). The traditional face swapping methods rely on global feature extraction and …

DisentanglementFace SwappingFacial EditingFacial Inpainting+1

Robust Sequential DeepFake Detection

2023-09-26 · Rui Shao, Tianxing Wu, Ziwei Liu

Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous deepfake detection methods are thus pro…

DeepFake DetectionFace SwappingFacial Editing

RIGID: Recurrent GAN Inversion and Editing of Real Face Videos

2023-08-11 · ICCV 2023 1 · Yangyang Xu, Shengfeng He, Kwan-Yee K. Wong, Ping Luo

GAN inversion is indispensable for applying the powerful editability of GAN to real images. However, existing methods invert video frames individually often leading to undesired inconsistent results over time. In this pa…

AttributeFacial EditingVideo Reconstruction

CHATEDIT: Towards Multi-turn Interactive Facial Image Editing via Dialogue

2023-03-20 · Xing Cui, Zekun Li, Peipei Li, Yibo Hu 외

This paper explores interactive facial image editing via dialogue and introduces the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this context. ChatEdit is constructed from the Ce…

AttributeFacial EditingResponse Generation

Detecting and Recovering Sequential DeepFake Manipulation

2022-07-05 · Rui Shao, Tianxing Wu, Ziwei Liu

Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous deepfake detection methods are thus pro…

DeepFake DetectionFace SwappingFacial EditingImage Captioning

Semantic Unfolding of StyleGAN Latent Space

2022-06-29 · Mustafa Shukor, Xu Yao, Bharath Bushan Damodaran, Pierre Hellier

Generative adversarial networks (GANs) have proven to be surprisingly efficient for image editing by inverting and manipulating the latent code corresponding to an input real image. This editing property emerges from the…

AttributeDisentanglementFacial Editing

Video2StyleGAN: Disentangling Local and Global Variations in a Video

2022-05-27 · Rameen Abdal, Peihao Zhu, Niloy J. Mitra, Peter Wonka

Image editing using a pretrained StyleGAN generator has emerged as a powerful paradigm for facial editing, providing disentangled controls over age, expression, illumination, etc. However, the approach cannot be directly…

Facial Editing

One-Shot Face Reenactment on Megapixels

2022-05-26 · Wonjun Kang, Geonsu Lee, Hyung Il Koo, Nam Ik Cho

The goal of face reenactment is to transfer a target expression and head pose to a source face while preserving the source identity. With the popularity of face-related applications, there has been much research on this …

Face GenerationFace ReenactmentFacial EditingTalking Face Generation+1

TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing

2022-03-31 · CVPR 2022 1 · Yanbo Xu, Yueqin Yin, Liming Jiang, Qianyi Wu 외

Recent advances like StyleGAN have promoted the growth of controllable facial editing. To address its core challenge of attribute decoupling in a single latent space, attempts have been made to adopt dual-space GAN for b…

AttributeDisentanglementFacial Editing

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN

2022-03-08 · Fei Yin, Yong Zhang, Xiaodong Cun, Mingdeng Cao 외

One-shot talking face generation aims at synthesizing a high-quality talking face video from an arbitrary portrait image, driven by a video or an audio segment. One challenging quality factor is the resolution of the out…

Face GenerationFacial EditingMotion GenerationTalking Face Generation+1

Stitch it in Time: GAN-Based Facial Editing of Real Videos

2022-01-20 · Rotem Tzaban, Ron Mokady, Rinon Gal, Amit H. Bermano 외

The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing. However, replicating their success with videos has proven challenging. S…

Facial Editing
1–20 / 29 다음 →