Cohesive Group Emotion Recognition

Submit the following details in a single PDF and your code in a Python Notebook in a zip file. 

• [PDF] Provide a clear description of the implementation process, including the technologies, frameworks, and libraries.
• [PDF] Describe how your solution will differentiate individual emotions within groups, highlighting the uniqueness of your approach, if any.
• Include a step-by-step explanation of how your solution processes group images and individualizes emotion recognition.
• [PDF] Specify how you integrate and adapt existing technologies to achieve the desired results.
• [PDF and Colab] Include preliminary results on some manually labeled data, demonstrating the effectiveness of your approach.
• Present any qualitative and quantitative measures used to evaluate the accuracy and nuance of individual emotion recognition within groups.
• Showcase comparisons with existing methods (if you explored multiple pre-trained models), emphasizing the improvements achieved by your solution.
• Provide a well-documented Colab-Notebook.
• Include clear instructions for running the code, along with any dependencies required.
• Document the code comprehensively to facilitate understanding and future development.
• Clearly label each section of your submission to enhance readability.
• [Optional] Include visualizations, diagrams, or flowcharts illustrating the workflow of your solution. If possible, provide demonstrations or screenshots showcasing your solution in action, highlighting its effectiveness in recognizing individual emotions within groups.
• [PDF] Challenges Faced and Solutions:
• Discuss any challenges encountered during the development process and the innovative solutions you implemented to overcome them.
• Provide insights into potential future enhancements for your solution, addressing any limitations and proposing strategies for improvement.