The recent wave of AI-generated content (AIGC) has witnessed substantial success in
computer vision, with the diffusion model playing a crucial role in this achievement. Due to …

The pursuit of controllability as a higher standard of visual content creation has yielded
remarkable progress in customizable image synthesis. However, achieving controllable …

Video-P2P is the first framework for real-world video editing with cross-attention control.
While attention control has proven effective for image editing with pre-trained image …

Large text-to-image diffusion models have exhibited impressive proficiency in generating
high-quality images. However, when applying these models to video domain, ensuring …

We present the content deformation field (CoDeF) as a new type of video representation
which consists of a canonical content field aggregating the static contents in the entire video …

Text-driven diffusion models have unlocked unprecedented abilities in image generation,
whereas their video counterpart still lags behind due to the excessive training cost of …

Video generation has witnessed significant advancements yet evaluating these models
remains a challenge. A comprehensive evaluation benchmark for video generation is …

Text-to-video is a rapidly growing research area that aims to generate a semantic, identical,
and temporal coherence sequence of frames that accurately align with the input text prompt …

We present VideoPoet, a language model capable of synthesizing high-quality video, with
matching audio, from a large variety of conditioning signals. VideoPoet employs a decoder …

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality
images from detailed textual descriptions, they often lack the ability to precisely edit the …