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[Bio]
[Blog]
[CS 297 Proposal]
[Deliverable 1]
[Rapid Object Detection using a Boosted Cascade of Simple Features-PDF]
[Deliverable 2]
[Deliverable 3-PDF]
[Deliverable 4]
[CS297 Report-PDF]
[CS298 Proposal]
[CS298 Report-PDF]
[CS298 Defense Slides-PDF]
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Project Blog
CS 298
Week 16: Mar 18, 2021
Minutes
- Defense Scheduled and Approved
Week 15: May 11, 2021
Minutes
- Review of CS298 Defense Slides
TODO:
- Incorporate the changes suggested
Week 14: May 4, 2021
Minutes
TODO:
- Incorporate the changes suggested
Week 13: Apr 27, 2021
Minutes
- Showed the implementation of the Attention Model
- Showed the final implementation of the whole model (Encoder + Decoder): Action Classifier and Heatmap Decoder
TODO:
- Change the layers in Attention Model and perform experiments
Week 12: Apr 20, 2021
Minutes
- Showed the design of added Attention Model in Encoder
TODO:
- Complete the whole architecture of the model
- Perform the changes suggested in the CS298 Draft Report
Week 11: Apr 13, 2021
Minutes
- Discuss the problem of poor model learning
TODO:
- Incorporate Attention Model to solve the model performance
- Start the first draft of Report
Week 10: Apr 6, 2021
Minutes
- Showed the implementation of Heatmap Predictor
- Discussed the error of noise in results of Heatmap
TODO:
- Fix the error in the heatmap model by changing its architecture
Week 9: Mar 30, 2021
Minutes
- Discussed the architecture of Fully convolutional neural network with Transposed Convolution layer for heatmap predictor
TODO:
- Implement the discussed architecture
Week 8: Mar 23, 2021
Minutes
- Showed and discussed the plausible design of classification model(Parallel Encoder + ConvLSTM)
TODO:
- Fix the error in the classification model and implement it
Week 7: Mar 16, 2021
Minutes
- Showed the implementation of CNN and ConvLSTM in parallel for the encoder model
- CNN used for spatial information and ConvLSTM used for temporal information
- CNN takes the input of last observed frame and ConvLSTM takes input of the difference between consecutive video frames
TODO:
- Completion of encoder model
- Work on decoder model
Week 5 - 6: Mar 1 to Mar 9, 2021
Minutes
- Discussed the ways of implementing parallel processing in encoder
- Discussed the possible ways to get the difference among video frames for the encoder input
TODO:
- Try getting the difference among video frames using ffmpeg
- Implement the parallel processing for encoder model
Week 4 - Feb 23, 2021
Minutes
- Discussed in-depth functionality of Demo2Vec encoder and decoder
TODO:
- Continue working on the Demo2Vec encoder
Week 3 - Feb 16, 2021
Minutes
- Showed the improvement in Humanoid's hand through Mixamo animations
TODO:
- Continue working on the Demo2Vec encoder
- Discuss how the encoder and decoder is going to work in the model
Week 2 - Feb 9, 2021
Minutes
- Showed the crooked hand of humanoid in dataset
- Discussed plausible solutions and future plans
TODO:
- Try to find a solution to fix the crooked hand of humanoid(Ethan)
Week 1 - Feb 2, 2021
Minutes
- Showed and got CS298 - Proposal approved
- Mentioned corrections required in the report and on the website
TODO:
- Work on the comments mentioned for the proposal and get add-code
CS297
Week 16 - Dec 8, 2020
Minutes
- Showed CS297-Report
- Mentioned corrections required in the report and on the website
TODO:
- Work on the comments mentioned for the report
Week 15 - Dec 1, 2020
Minutes
- Worked towards and debugged OPRA dataset of Demo2Vec
- Discussed ConvLSTM developed to handle video clips generated from OPRA dataset
TODO:
Week 14 - Nov 24, 2020
Minutes
- Implemented Human Activity recognition on dataset UCF and HDMB to understand how to input video frames into model
- Created two models, one model by extracting features from VVG16 and then passing them to convolutional layers and the other time series ConvLSTM model
TODO:
- Work on implementing Demo2Vec model
Week 13 - Nov 17, 2020
Minutes
- Showed movies of multiple scenes with multiple camera positions
- Discussed various affordance papers and looked into Demo2Vec
TODO:
- Try to implement simple neural network on video dataset similar to Demo2Vec
Week 12 - Nov 10, 2020
Minutes
- Showed multiple scenes with multiple variations in the position of the 3D player(Ethan) and the position of pickable objects(like book, food etc.) in a room.
- Showed the progress of Extended Deliverable 2
- Showed video made out of multiple scenes and showed how the transitioning of scenes is happening with the script
- Discussed how to make the whole dataset automated without the involvement of keys
- Discussed the approach of using different camera positions to make 50 videos faster using script
TODO:
- Continue working on Deliverable 2 (different camera positions)
- Look into the researches going on in visual affordance
Week 11 - Nov 3, 2020
Minutes
- Showed scene consisting of a 3D player(Ethan) and multiple objects(like book, food etc.) in a room.
- Showed how player is able to walk towards the object and pick it using script
- Recorded video of the whole scene
- Deliverable 2 extended, create 50 videos of the scene using script
TODO:
- Work on Extension of Deliverable 2
Week 10 - Oct 27, 2020
Minutes
- Showed partial progress(placed objects and player to create an environment in Unity) of Deliverable 2
- Discussed the plausible approach to reach the results of Deliverable 2
TODO:
- Continuing working towards Deliverable 2
Week 9 - Oct 20, 2020
Minutes
- Updated the progress on Unity
- Discussed and resolved doubts regarding Deliverable 2
TODO:
- Working towards Deliverable 2
Week 8 - Oct 13, 2020
Minutes
- Showed the final model for object detection and classification of multi class in a single image using OpenCV and
Keras
- Deliverable 1 accepted
TODO:
Week 7 - Oct 6, 2020
Minutes
- Showed model for object classification of multi class in a single image
- Re-scoping the Deliverable to 2 phases: Emoji detection with Open CV and Emoji classification with Keras
- Changes suggested in object classification model
TODO:
- Divide the Deliverable into 2 phases
- Incorporate the changes suggested
Week 6 - Sept 29, 2020
Minutes
- Showed object detection and classification of 1 class in a single image
- Presented Paper 1
- Improvements suggested in Presentation of Paper 1
TODO:
- Aim in making Object detection and classification multi-class
Week 5 - Sept 22, 2020
Minutes
- Discussed possible approaches about Deliverable 1
- Resolved issues regarding Deliverable 1
- Paper suggested to study the technique used to detect objects without bounding boxes annotations(Paper 2)
TODO:
- Progress on Deliverable 1
- Presentation of Paper 1
Week 4 - Sept 15, 2020
Minutes
- Showed object detection using OpenCV
- Paper suggested to study the technique used to detect objects with OpenCV (Paper 1)
TODO:
- Perform image classification using Pytorch
- Complete Deliverable 1
Week 3 - Sept 8, 2020
Minutes
- Updated the level of learning
- Discussed changes and modifications in Deliverable 1
TODO:
- Continue with learning OpenCV and Pytorch
- Work towards deliverable#1
Week 2 - Sept 1, 2020
Minutes
- Finalized CS297 topic
- Discussed upcoming deliverables and possible scope of project
TODO:
- Update proposal
- Work towards deliverable#1
Week 1 - Aug 25, 2020
Minutes
- First meeting to discuss possible topics
- Topics discussed:-
- Detect and predict affordance in a room
- Mine Wiki data
- Mine pattern among different mutations of disease using association rules
- Compute K-means of neighboring data nodes in distributed network
TODO:
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