# BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AI

arXiv: https://arxiv.org/abs/2403.13947 · HTML: https://mlsanity.com/paper/2403.13947/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 69 references that are in the map.
- First posted on arXiv 20 Mar 2024.

## Builds on (most cited first, 15 of 15)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Free-Form Image Inpainting with Gated Convolution](https://mlsanity.com/paper/1806.03589/) (2018)
- [Shap-E: Generating Conditional 3D Implicit Functions](https://mlsanity.com/paper/2305.02463/) (2023)
- [Real-Time User-Guided Image Colorization with Learned Deep Priors](https://mlsanity.com/paper/1705.02999/) (2017)
- [HoloDiffusion: Training a 3D Diffusion Model using 2D Images](https://mlsanity.com/paper/2303.16509/) (2023)
- [PanoGen: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation](https://mlsanity.com/paper/2305.19195/) (2023)
- [Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction](https://mlsanity.com/paper/1811.09845/) (2018)
- [Opal: Multimodal Image Generation for News Illustration](https://mlsanity.com/paper/2204.09007/) (2022)
- [PromptPaint: Steering Text-to-Image Generation Through Paint Medium-like Interactions](https://mlsanity.com/paper/2308.05184/) (2023)
- [Simple and Effective Synthesis of Indoor 3D Scenes](https://mlsanity.com/paper/2204.02960/) (2022)
- [ChatPainter: Improving Text to Image Generation using Dialogue](https://mlsanity.com/paper/1802.08216/) (2018)
- [GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information](https://mlsanity.com/paper/2202.00965/) (2022)
- [WorldSmith: Iterative and Expressive Prompting for World Building with a Generative AI](https://mlsanity.com/paper/2308.13355/) (2023)
- [MeetScript: Designing Transcript-based Interactions to Support Active Participation in Group Video Meetings](https://mlsanity.com/paper/2309.12115/) (2023)

## Built on by (most cited first, 3 of 3)

- [SpaceBlender: Creating Context-Rich Collaborative Spaces Through Generative 3D Scene Blending](https://mlsanity.com/paper/2409.13926/) (2024)
- [When Generative Artificial Intelligence meets Extended Reality: A Systematic Review](https://mlsanity.com/paper/2511.03282/) (2025)
- [Generative Tutorial: Towards Live Contextualized Visual Instructions for Physical Tasks](https://mlsanity.com/paper/2609.24955/) (2026)

## Abstract (arXiv)

Today's video-conferencing tools support a rich range of professional and social activities, but their generic meeting environments cannot be dynamically adapted to align with distributed collaborators' needs. To enable end-user customization, we developed BlendScape, a rendering and composition system for video-conferencing participants to tailor environments to their meeting context by leveraging AI image generation techniques. BlendScape supports flexible representations of task spaces by blending users' physical or digital backgrounds into unified environments and implements multimodal interaction techniques to steer the generation. Through an exploratory study with 15 end-users, we investigated whether and how they would find value in using generative AI to customize video-conferencing environments. Participants envisioned using a system like BlendScape to facilitate collaborative activities in the future, but required further controls to mitigate distracting or unrealistic visual elements. We implemented scenarios to demonstrate BlendScape's expressiveness for supporting environment design strategies from prior work and propose composition techniques to improve the quality of environments.