VideoCrafter2: A groundbreaking method that crafts videos from a given text prompt. Researchers from Tencent AI Lab presented this outstanding model. The model takes text prompt as an input and generate output in the form of videos. The generated videos are of high quality giving unparalleled precision and visual excellence.
Models for creating high-quality videos from text have shown remarkable progress in recent years. However, these models usually need a lot of top-notch videos, which is not easily accessible to everyone. Many researchers utilized WebVid-10M dataset which has lower quality videos for training purpose and these models struggle to generate high quality videos because of their limitations.
To overcome these limitations, researchers from Tencent AI Lab presented VideoCrafter2. In this model the researchers tried to overcome the issue of not having enough high-quality data to train the video models. For this, they separate the motion (how objects should move) from appearance (how objects should be presented). Through this separation, the process of training the model becomes more focused about how objects should move and how object should appear. Because of this, even with the limited high-quality data, VideoCrafter2 can still able to understand and generate high-quality videos.
In VideoCrafter2, some important factors to create high quality videos were investigated. The basic and key factor is the relationship between spatial (related to space and appearance) and temporal (related to time and motion). The researchers also tried to understand that which type of videos should be used in the training process that affects the quality of the resulting videos.
Based on the above mentioned observations, the process of VideoCrafter2 consists of two main steps; first, the video model was trained from the scratch, making sure it learns from diverse field of data to make it capable enough. Second, the spatial module was fine-tuned using high quality images. These two steps aids to achieve a high quality video generation model to create a strong foundation.
While using the demo of VideoCrafter2 at the HuggingFace, the text prompt “Cute Brown Bear in Snow”. The model has the ability to expand the user input in more detail. Below is the video generated by user prompt.
The model expand the user prompt into rich prompt “Photography, Adorable bear cub, frolicking in pristine snow, soft-focus, serene winter landscape, ethereal glow, high-definition quality.” Below is the video generated from rich prompt by VideoCrafter2 which more detailed.
Why VideoCrafter2?
The researchers faced challenges for not having enough high quality data for training extraordinary video models. So, different parts of video models more specifically spatial and temporal modules were studied closely for training purpose using Stable Diffusion Model.
After having good understanding, a step-by-step process was created for training high quality video model while having low quality videos and high quality images while training. The separate understanding of temporal and spatial module makes it easier to create high quality and impressive videos.
VideoCrafter2 models has the capability of revolutionizing various industries, from infotainment and marketing to research and education. In the field of content creation, it can be used to create compelling videos. It can be utilized from virtual to augmented reality and beyond while amplifying the interactive experience for users.
Above added snip is the comparison of VideoCrafter1 with VideoCrafter2. This latest model is generating extremely high quality and impressive outcome.
Wrap Up!
From extensive qualitative and quantitative evaluation, it is concluded that the effectiveness of visual quality of VideoCrafter2 is comparable to VideoCrafter1 and Pika Labs which is capable of generating high fidelity videos with exceptional aesthetics. It also surpasses Show-1 in terms of motion quality.
References
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