# InterAct: Capture and Modelling of Realistic, Expressive and Interactive Activities between Two Persons in Daily Scenarios

arXiv: https://arxiv.org/abs/2405.11690 · HTML: https://mlsanity.com/paper/2405.11690/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 44 references that are in the map.
- First posted on arXiv 19 May 2024.

## Builds on (most cited first, 28 of 28)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [Deep Unsupervised Learning using Nonequilibrium Thermodynamics](https://mlsanity.com/paper/1503.03585/) (2015)
- [Generative Modeling by Estimating Gradients of the Data Distribution](https://mlsanity.com/paper/1907.05600/) (2019)
- [Human Motion Diffusion Model](https://mlsanity.com/paper/2209.14916/) (2022)
- [AdapterHub: A Framework for Adapting Transformers](https://mlsanity.com/paper/2007.07779/) (2020)
- [Capture, Learning, and Synthesis of 3D Speaking Styles](https://mlsanity.com/paper/1905.03079/) (2019)
- [FaceFormer: Speech-Driven 3D Facial Animation with Transformers](https://mlsanity.com/paper/2112.05329/) (2021)
- [Learning Individual Styles of Conversational Gesture](https://mlsanity.com/paper/1906.04160/) (2019)
- [MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement](https://mlsanity.com/paper/2104.08223/) (2021)
- [Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models](https://mlsanity.com/paper/2211.09707/) (2022)
- [CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior](https://mlsanity.com/paper/2301.02379/) (2023)
- [Generating Holistic 3D Human Motion from Speech](https://mlsanity.com/paper/2212.04420/) (2022)
- [BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis](https://mlsanity.com/paper/2203.05297/) (2022)
- [GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents](https://mlsanity.com/paper/2303.14613/) (2023)
- [EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation](https://mlsanity.com/paper/2303.11089/) (2023)
- [Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion](https://mlsanity.com/paper/2204.08451/) (2022)
- [Emotional Speech-Driven Animation with Content-Emotion Disentanglement](https://mlsanity.com/paper/2306.08990/) (2023)
- [Inter-X: Towards Versatile Human-Human Interaction Analysis](https://mlsanity.com/paper/2312.16051/) (2023)
- [Hi4D: 4D Instance Segmentation of Close Human Interaction](https://mlsanity.com/paper/2303.15380/) (2023)
- [ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech](https://mlsanity.com/paper/2209.07556/) (2022)
- [From Audio to Photoreal Embodiment: Synthesizing Humans in Conversations](https://mlsanity.com/paper/2401.01885/) (2024)
- [FaceDiffuser: Speech-Driven 3D Facial Animation Synthesis Using Diffusion](https://mlsanity.com/paper/2309.11306/) (2023)
- [Can Language Models Learn to Listen?](https://mlsanity.com/paper/2308.10897/) (2023)
- [Body2Hands: Learning to Infer 3D Hands from Conversational Gesture Body Dynamics](https://mlsanity.com/paper/2007.12287/) (2020)
- [BodyFormer: Semantics-guided 3D Body Gesture Synthesis with Transformer](https://mlsanity.com/paper/2310.06851/) (2023)
- [DiffSpeaker: Speech-Driven 3D Facial Animation with Diffusion Transformer](https://mlsanity.com/paper/2402.05712/) (2024)
- [Joint Audio-Text Model for Expressive Speech-Driven 3D Facial Animation](https://mlsanity.com/paper/2112.02214/) (2021)

## Built on by (most cited first, 7 of 7)

- [INFP: Audio-Driven Interactive Head Generation in Dyadic Conversations](https://mlsanity.com/paper/2412.04037/) (2024)
- [ARIG: Autoregressive Interactive Head Generation for Real-time Conversations](https://mlsanity.com/paper/2507.00472/) (2025)
- [SocialGen: Modeling Multi-Human Social Interaction with Language Models](https://mlsanity.com/paper/2503.22906/) (2025)
- [MOSPA: Human Motion Generation Driven by Spatial Audio](https://mlsanity.com/paper/2507.11949/) (2025)
- [Social Agent: Mastering Dyadic Nonverbal Behavior Generation via Conversational LLM Agents](https://mlsanity.com/paper/2510.04637/) (2025)
- [DyStream: Streaming Dyadic Talking Heads Generation via Flow Matching-based Autoregressive Model](https://mlsanity.com/paper/2512.24408/) (2025)
- [PhysiInter: Integrating Physical Mapping for High-Fidelity Human Interaction Generation](https://mlsanity.com/paper/2506.07456/) (2025)

## Abstract (arXiv)

We address the problem of accurate capture and expressive modelling of interactive behaviors happening between two persons in daily scenarios. Different from previous works which either only consider one person or focus on conversational gestures, we propose to simultaneously model the activities of two persons, and target objective-driven, dynamic, and coherent interactions which often span long duration. To this end, we capture a new dataset dubbed InterAct, which is composed of 241 motion sequences where two persons perform a realistic scenario over the whole sequence. The audios, body motions, and facial expressions of both persons are all captured in our dataset. We also demonstrate the first diffusion model based approach that directly estimates the interactive motions between two persons from their audios alone. All the data and code will be available at: https://hku-cg.github.io/interact.