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Found 7 papers, 3 papers with code
TrailBlazer: Trajectory Control for Diffusion-Based Video Generation
Within recent approaches to text-to-video (T2V) generation, achieving controllability in the synthesized video is often a challenge.
FDLS: A Deep Learning Approach to Production Quality, Controllable, and Retargetable Facial Performances
This paper describes FDLS (Facial Deep Learning Solver), which is Weta Digital's solution to these challenges.
Exact Diffusion Inversion via Bi-directional Integration Approximation
In our work, it is found that applying BDIA to the EDM sampling procedure produces consistently better performance over four pre-trained models.
Training-Free Neural Matte Extraction for Visual Effects
Alpha matting is widely used in video conferencing as well as in movies, television, and social media sites.
Directed Diffusion: Direct Control of Object Placement through Attention Guidance
Text-guided diffusion models such as DALLE-2, Imagen, eDiff-I, and Stable Diffusion are able to generate an effectively endless variety of images given only a short text prompt describing the desired image content.
The HSIC Bottleneck: Deep Learning without Back-Propagation
We introduce the HSIC (Hilbert-Schmidt independence criterion) bottleneck for training deep neural networks.
A Database and Evaluation Methodology for Optical Flow
The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance.
