30 citations · 49 across the 16 of their papers we have counts for
6 papers · 1 filter
Movie Gen: A Cast of Media Foundation Models
Adam Polyak, Amit Zohar, Andrew Brown +85
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…
Imagine yourself: Tuning-Free Personalized Image Generation
Zecheng He, Bo Sun, Felix Juefei-Xu +14
Diffusion models have demonstrated remarkable efficacy across various image-to-image tasks. In this research, we introduce Imagine yourself, a state-of-the-art model designed for p…
Imagine Flash: Accelerating Emu Diffusion Models with Backward Distillation
Jonas Kohler, Albert Pumarola, Edgar Schönfeld +4
Diffusion models are a powerful generative framework, but come with expensive inference. Existing acceleration methods often compromise image quality or fail under complex conditio…
Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack
Xiaoliang Dai, Ji Hou, Chih-Yao Ma +23
Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face chal…
EgoObjects: A Large-Scale Egocentric Dataset for Fine-Grained Object Understanding
Chenchen Zhu, Fanyi Xiao, Andres Alvarado +6
Object understanding in egocentric visual data is arguably a fundamental research topic in egocentric vision. However, existing object datasets are either non-egocentric or have li…
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding
Lorenzo Pellegrini, Chenchen Zhu, Fanyi Xiao +7
Continual Learning, also known as Lifelong or Incremental Learning, has recently gained renewed interest among the Artificial Intelligence research community. Recent research effor…