6 citations · 6 across the 4 of their papers we have counts for
4 papers
VIMI: Grounding Video Generation through Multi-modal Instruction
Yuwei Fang, Willi Menapace, Aliaksandr Siarohin +5
Existing text-to-video diffusion models rely solely on text-only encoders for their pretraining. This limitation stems from the absence of large-scale multimodal prompt video datas…
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace +8
The quality of the data and annotation upper-bounds the quality of a downstream model. While there exist large text corpora and image-text pairs, high-quality video-text data is mu…
Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis
Willi Menapace, Aliaksandr Siarohin, Ivan Skorokhodov +8
Contemporary models for generating images show remarkable quality and versatility. Swayed by these advantages, the research community repurposes them to generate videos. Since vide…
Motion-Conditioned Diffusion Model for Controllable Video Synthesis
Tsai-Shien Chen, Chieh Hubert Lin, Hung-Yu Tseng +2
Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers hav…