Cover Image

IP-Adapter Is All You Need: Towards Fine-Tuning-Free Diffusion-Based Talking Face Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Hao, Luo, Xiangyang, Wang, Hao, Zhang, Jiawei, Zhang, Yi, Wang, Jinwei
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Joint Co-Speech Gesture and Expressive Talking Face Generation using Diffusion with Adapters
by: Hogue, Steven, et al.
Published: (2024)

AuthFace: Towards Authentic Blind Face Restoration with Face-oriented Generative Diffusion Prior
by: Liang, Guoqiang, et al.
Published: (2024)

Text-Driven Emotionally Continuous Talking Face Generation
by: Yang, Hao, et al.
Published: (2026)

Generalize Your Face Forgery Detectors: An Insertable Adaptation Module Is All You Need
by: Si, Xiaotian, et al.
Published: (2024)

SMPL Normal Map Is All You Need for Single-view Textured Human Reconstruction
by: Shen, Wenhao, et al.
Published: (2025)

Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control
by: Han, Yue, et al.
Published: (2024)

Similarity Memory Prior is All You Need for Medical Image Segmentation
by: Tang, Hao, et al.
Published: (2025)

Mixture of Physical Priors Adapter for Parameter-Efficient Fine-Tuning
by: Wang, Zhaozhi, et al.
Published: (2024)

Pseudo Anomalies Are All You Need: Diffusion-Based Generation for Weakly-Supervised Video Anomaly Detection
by: Hashimoto, Satoshi, et al.
Published: (2025)

Ideal Registration? Segmentation is All You Need
by: Chen, Xiang, et al.
Published: (2025)

PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation
by: Wang, Baiqin, et al.
Published: (2025)

FineVision: Open Data Is All You Need
by: Wiedmann, Luis, et al.
Published: (2025)

Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-grained Control
by: Chen, Hejia, et al.
Published: (2025)

GLCF: A Global-Local Multimodal Coherence Analysis Framework for Talking Face Generation Detection
by: Chen, Xiaocan, et al.
Published: (2024)

ParameterNet: Parameters Are All You Need
by: Han, Kai, et al.
Published: (2023)

Training-Free Synthetic Data Generation with Dual IP-Adapter Guidance
by: Boudier, Luc, et al.
Published: (2025)

Emu3: Next-Token Prediction is All You Need
by: Wang, Xinlong, et al.
Published: (2024)

CPA: Camera-pose-awareness Diffusion Transformer for Video Generation
by: Wang, Yuelei, et al.
Published: (2024)

G4G:A Generic Framework for High Fidelity Talking Face Generation with Fine-grained Intra-modal Alignment
by: Zhang, Juan, et al.
Published: (2024)

Beyond Graph Model: Reliable VLM Fine-Tuning via Random Graph Adapter
by: Jiang, Bo, et al.
Published: (2025)

Towards Real-World Blind Face Restoration with Generative Diffusion Prior
by: Chen, Xiaoxu, et al.
Published: (2023)

EmoTalker: Emotionally Editable Talking Face Generation via Diffusion Model
by: Zhang, Bingyuan, et al.
Published: (2024)

RestorerID: Towards Tuning-Free Face Restoration with ID Preservation
by: Ying, Jiacheng, et al.
Published: (2024)

DisentTalk: Cross-lingual Talking Face Generation via Semantic Disentangled Diffusion Model
by: Liu, Kangwei, et al.
Published: (2025)

Attn-Adapter: Attention Is All You Need for Online Few-shot Learner of Vision-Language Model
by: Bui, Phuoc-Nguyen, et al.
Published: (2025)

Safeguarding Facial Identity against Diffusion-based Face Swapping via Cascading Pathway Disruption
by: Wang, Liqin, et al.
Published: (2026)

Search is All You Need for Few-shot Anomaly Detection
by: Wang, Qishan, et al.
Published: (2025)

DreamTalk: When Emotional Talking Head Generation Meets Diffusion Probabilistic Models
by: Ma, Yifeng, et al.
Published: (2023)

Performance is not All You Need: Sustainability Considerations for Algorithms
by: Li, Xiang, et al.
Published: (2025)

Are Foundation Models All You Need for Zero-shot Face Presentation Attack Detection?
by: Gonzalez-Sole, Lazaro Janier, et al.
Published: (2025)

Mod-Adapter: Tuning-Free and Versatile Multi-concept Personalization via Modulation Adapter
by: Zhong, Weizhi, et al.
Published: (2025)

Taming Transformer for Emotion-Controllable Talking Face Generation
by: Zhang, Ziqi, et al.
Published: (2025)

Adapter-X: A Novel General Parameter-Efficient Fine-Tuning Framework for Vision
by: Li, Minglei, et al.
Published: (2024)

Context-aware Talking Face Video Generation
by: Xuanyuan, Meidai, et al.
Published: (2024)

EasyTune: Efficient Step-Aware Fine-Tuning for Diffusion-Based Motion Generation
by: Tan, Xiaofeng, et al.
Published: (2026)

MuseFace: Text-driven Face Editing via Diffusion-based Mask Generation Approach
by: Zhang, Xin, et al.
Published: (2025)

One Snapshot is All You Need: A Generalized Method for mmWave Signal Generation
by: Huang, Teng, et al.
Published: (2025)

The Right Inference Strategy Is All You Need: Nearly Training-Free Domain-Wise Inference for EgoCross Challenge
by: Wu, Leyi, et al.
Published: (2026)

DynaIP: Dynamic Image Prompt Adapter for Scalable Zero-shot Personalized Text-to-Image Generation
by: Wang, Zhizhong, et al.
Published: (2025)

SVAC: Scaling Is All You Need For Referring Video Object Segmentation
by: Zhang, Li, et al.
Published: (2025)