StreamEval:交互式流式视频生成模型评测基准
原标题:Paper page - StreamEval: Evaluating Interactive Streaming Video Generation Models
AI 摘要
研究团队提出 StreamEval,这是首个面向交互式流式视频生成的统一基准,覆盖虚拟人对话、虚拟人表演、世界生成、指令编辑和参考编辑五类任务,包含 300 个时长 15-300 秒的脚本化测试用例,并从任务执行、状态一致性、视觉保真度和视听协调四个维度评估。对 37 个模型的评测显示,高视觉质量与身份保持并不等同于可靠的请求执行或持续的状态一致性,任务执行得分普遍偏低,例如虚拟人表演的 Following 最高仅 36.90。研究结论指出,在时序与内容保持约束下可靠执行请求,是推进全模态实时交互系统的核心挑战。
正文节选
StreamEval: Evaluating Interactive Streaming Video Generation Models Abstract StreamEval benchmarks interactive streaming video generation across five tasks, revealing that reliable request execution and sustained state consistency remain major challenges despite high visual quality. As streaming video generation advances, enabling real-time interaction with generated video is becoming increasingly important. We introduce StreamEval, a unified benchmark for interactive streaming video generation