
## Emotion-Controllable Generalized Talking Face Generation
Sanjana Sinha, Sandika Biswas, Ravindra Yadav, Brojeshwar Bhowmick
Keywords: Computer Vision: Applications, Computer Vision: Machine Learning for Vision, Computer Vision: Neural generative models, auto encoders, GANs, Humans and AI: Human-Computer Interaction, Machine Learning: Applications
IJCAI/2022/Proceedings/0184 - Emotion-Controllable Generalized Talking Face Generation.pdf

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[8]

The authors do not share their implementation. They state they use the PyTorch framework in 4.2. Their proposed method is detailed in figure 2. 

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[4]

(3/3)

The authors state they use 3 datasets and provide citations on them. They are all public. There are no descriptions or statistics, only a statement on data selection from MEAD. No direct link provided. 

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[7]

The authors state a few hyperparmaeter values in 4.2. But a full summary on all HPs considered is not found. It is also not specified how these values were acquired. There are only very few values stated. 

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[2]

The authors evaluate their method on the static test splits of each data set, but only train on the data of MEAD. The authors state the metrics used with citation in 4.3. and a small description but a full explanation is missing. The results are single run.

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[5]

Requires expertise with CV and gen AI / GANs.
