# MFR-Net: Multi-faceted Responsive Listening Head Generation via Denoising Diffusion Model

arXiv: https://arxiv.org/abs/2308.16635 · HTML: https://mlsanity.com/paper/2308.16635/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- Placed in Audio, speech and music, one of 14 directions in Diffusion models.
- Builds on 40 of its 52 references that are in the map.
- First posted on arXiv 31 Aug 2023.

## Placed in

- Diffusion models / [Audio, speech and music](https://mlsanity.com/diffusion/audio-speech-and-music/)

## Builds on (most cited first, 30 of 40)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://mlsanity.com/paper/2204.06125/) (2022)
- [Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding](https://mlsanity.com/paper/2205.11487/) (2022)
- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [Improved Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2102.09672/) (2021)
- [GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://mlsanity.com/paper/2112.10741/) (2021)
- [Semantic Image Synthesis with Spatially-Adaptive Normalization](https://mlsanity.com/paper/1903.07291/) (2019)
- [VGGFace2: A dataset for recognising faces across pose and age](https://mlsanity.com/paper/1710.08092/) (2017)
- [A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild](https://mlsanity.com/paper/2008.10010/) (2020)
- [Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set](https://mlsanity.com/paper/1903.08527/) (2019)
- [U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection](https://mlsanity.com/paper/2005.09007/) (2020)
- [AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://mlsanity.com/paper/2103.11078/) (2021)
- [Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation](https://mlsanity.com/paper/2104.11116/) (2021)
- [Hierarchical Cross-Modal Talking Face Generationwith Dynamic Pixel-Wise Loss](https://mlsanity.com/paper/1905.03820/) (2019)
- [The Creation and Detection of Deepfakes: A Survey](https://mlsanity.com/paper/2004.11138/) (2020)
- [FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping](https://mlsanity.com/paper/1912.13457/) (2019)
- [Talking Face Generation by Adversarially Disentangled Audio-Visual Representation](https://mlsanity.com/paper/1807.07860/) (2018)
- [PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering](https://mlsanity.com/paper/2109.08379/) (2021)
- [Audio-Driven Emotional Video Portraits](https://mlsanity.com/paper/2104.07452/) (2021)
- [Fine-Grained Head Pose Estimation Without Keypoints](https://mlsanity.com/paper/1710.00925/) (2017)
- [EAMM: One-Shot Emotional Talking Face via Audio-Based Emotion-Aware Motion Model](https://mlsanity.com/paper/2205.15278/) (2022)
- [Talking-head Generation with Rhythmic Head Motion](https://mlsanity.com/paper/2007.08547/) (2020)
- [VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild](https://mlsanity.com/paper/2211.14758/) (2022)
- [Text-based Editing of Talking-head Video](https://mlsanity.com/paper/1906.01524/) (2019)
- [Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis](https://mlsanity.com/paper/2211.14506/) (2022)
- [FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning](https://mlsanity.com/paper/2108.07938/) (2021)

## Built on by (most cited first, 16 of 16)

- [INFP: Audio-Driven Interactive Head Generation in Dyadic Conversations](https://mlsanity.com/paper/2412.04037/) (2024)
- [DualTalk: Dual-Speaker Interaction for 3D Talking Head Conversations](https://mlsanity.com/paper/2505.18096/) (2025)
- [CustomListener: Text-guided Responsive Interaction for User-friendly Listening Head Generation](https://mlsanity.com/paper/2403.00274/) (2024)
- [Avatar Forcing: Real-Time Interactive Head Avatar Generation for Natural Conversation](https://mlsanity.com/paper/2601.00664/) (2026)
- [ARIG: Autoregressive Interactive Head Generation for Real-time Conversations](https://mlsanity.com/paper/2507.00472/) (2025)
- [Beyond Talking -- Generating Holistic 3D Human Dyadic Motion for Communication](https://mlsanity.com/paper/2403.19467/) (2024)
- [Edit-Your-Motion: Space-Time Diffusion Decoupling Learning for Video Motion Editing](https://mlsanity.com/paper/2405.04496/) (2024)
- [DiTaiListener: Controllable High Fidelity Listener Video Generation with Diffusion](https://mlsanity.com/paper/2504.04010/) (2025)
- [Model Will Tell: Training Membership Inference for Diffusion Models](https://mlsanity.com/paper/2403.08487/) (2024)
- [Towards Seamless Interaction: Causal Turn-Level Modeling of Interactive 3D Conversational Head Dynamics](https://mlsanity.com/paper/2512.15340/) (2025)
- [VividListener: Expressive and Controllable Listener Dynamics Modeling for Multi-Modal Responsive Interaction](https://mlsanity.com/paper/2504.21718/) (2025)
- [Warm Chat: Diffuse Emotion-aware Interactive Talking Head Avatar with Tree-Structured Guidance](https://mlsanity.com/paper/2508.18337/) (2025)
- [Talking Together: Synthesizing Co-Located 3D Conversations from Audio](https://mlsanity.com/paper/2603.08674/) (2026)
- [Resonant Minds: Closed-Loop Social Avatars with Theory of Mind](https://mlsanity.com/paper/2606.05896/) (2026)
- [InterSing: Explicit Interaction Dynamics for 3D Duet Singing Animation and Beyond](https://mlsanity.com/paper/2609.04903/) (2026)
- [ECHO: Dyadic 3D Facial Motion Generation with Asymmetric Deterministic Articulation and Stochastic Reaction](https://mlsanity.com/paper/2609.05506/) (2026)

## Abstract (arXiv)

Face-to-face communication is a common scenario including roles of speakers and listeners. Most existing research methods focus on producing speaker videos, while the generation of listener heads remains largely overlooked. Responsive listening head generation is an important task that aims to model face-to-face communication scenarios by generating a listener head video given a speaker video and a listener head image. An ideal generated responsive listening video should respond to the speaker with attitude or viewpoint expressing while maintaining diversity in interaction patterns and accuracy in listener identity information. To achieve this goal, we propose the Multi-Faceted Responsive Listening Head Generation Network (MFR-Net). Specifically, MFR-Net employs the probabilistic denoising diffusion model to predict diverse head pose and expression features. In order to perform multi-faceted response to the speaker video, while maintaining accurate listener identity preservation, we design the Feature Aggregation Module to boost listener identity features and fuse them with other speaker-related features. Finally, a renderer finetuned with identity consistency loss produces the final listening head videos. Our extensive experiments demonstrate that MFR-Net not only achieves multi-faceted responses in diversity and speaker identity information but also in attitude and viewpoint expression.