Today's video-conferencing tools support a rich range of professional and social activities, but their generic, grid-based environments cannot be easily adapted to meet the varying needs of distributed collaborators. To enable end-user customization, we developed BlendScape, a system for meeting participants to compose video-conferencing environments tailored to their collaboration context by leveraging AI image generation techniques. BlendScape supports flexible representations of task spaces by blending users' physical or virtual backgrounds into unified environments and implements multimodal interaction techniques to steer the generation. Through an evaluation with 15 end-users, we investigated their customization preferences for work and social scenarios. Participants could rapidly express their design intentions with BlendScape and envisioned using the system to structure collaboration in future meetings, but experienced challenges with preventing distracting elements. We implement scenarios to demonstrate BlendScape's expressiveness in supporting distributed collaboration techniques from prior work and propose composition techniques to improve the quality of environments.

翻译：当前的视频会议工具支持丰富的专业和社交活动，但其通用的网格化环境难以根据分布式协作者的多样化需求进行灵活调整。为实现终端用户定制化，我们开发了BlendScape系统——通过利用AI图像生成技术，使会议参与者能够根据协作场景构建量身定制的视频会议环境。该系统通过融合用户的物理或虚拟背景形成统一环境，支持任务空间的灵活表征，并实现多模态交互技术以引导生成过程。通过对15位终端用户的评估，我们探究了其在工作和社交场景下的定制偏好。参与者能够快速通过BlendScape表达设计意图，并构想将该系统用于未来会议的结构化协作，但也在防止干扰元素方面遇到挑战。我们通过多个场景验证了BlendScape在支持以往分布式协作技术方面的表现力，并提出环境质量优化组合技术。