Pinned Repositories
adityassrana.github.io
BITS-F312-Neural-Networks-and-Fuzzy-Logic
Archived Notebooks from Neural Networks course at BITS Pilani. Course website at https://bitsnnfl.github.io/
blog
https://adityassrana.github.io/blog
Content-Weighted-Image-Compression
PyTorch implementation of Learning Convolutional Networks for Content-Weighted Image Compression
fastai_playground
Experiments with things I learned while doing the fast.ai course.
MCV-M3-MLCV
Image classification - Bag of Visual Words, Keypoints and Descriptors, Spatial Pyramids, K-Means and GMM clustering, PCA, LDA, SVM, Fisher Vectors, Fine Tuning CNNs, Training CNNs from scratch.
MCV-M4-3DV
Implemented image warping, affine and metric rectification, DLT, RANSAC, panorama stitching Zhang’s calibration method, view morphing, stereo matching, depth-map computation, bundle adjustment and resectioning for Structure from Motion
multimodal-learning
RGBD-Scene Classification. Inroductory problem to get started with multimodal deep learning
object-detection-mnist
Toy problem to get started with object detection and bounding box regression using MNIST
pytorch-image-classification
A script to quickly evaluate image classification performance on different architectures, optimizers and datasetss
adityassrana's Repositories
adityassrana/Content-Weighted-Image-Compression
PyTorch implementation of Learning Convolutional Networks for Content-Weighted Image Compression
adityassrana/MCV-M4-3DV
Implemented image warping, affine and metric rectification, DLT, RANSAC, panorama stitching Zhang’s calibration method, view morphing, stereo matching, depth-map computation, bundle adjustment and resectioning for Structure from Motion
adityassrana/blog
https://adityassrana.github.io/blog
adityassrana/multimodal-learning
RGBD-Scene Classification. Inroductory problem to get started with multimodal deep learning
adityassrana/MCV-M3-MLCV
Image classification - Bag of Visual Words, Keypoints and Descriptors, Spatial Pyramids, K-Means and GMM clustering, PCA, LDA, SVM, Fisher Vectors, Fine Tuning CNNs, Training CNNs from scratch.
adityassrana/adityassrana.github.io
adityassrana/BITS-F312-Neural-Networks-and-Fuzzy-Logic
Archived Notebooks from Neural Networks course at BITS Pilani. Course website at https://bitsnnfl.github.io/
adityassrana/fastai_playground
Experiments with things I learned while doing the fast.ai course.
adityassrana/MCV-M1-IHCV
Content Based Image Retrieval. Implementations of color histograms, spatial pyramids, HOG, DCT, LBP, top hat and low hat filters, background and text removal, image denoising, and keypoints descriptors SIFT, SURF, ORB.
adityassrana/MCV-M2-OICV
Optimization in Computer Vision. Implementations of Image Inpainting, Poisson Editing, Chan-Vese Segmentation and Markov Random Fields for Image Segmentation.
adityassrana/object-detection-mnist
Toy problem to get started with object detection and bounding box regression using MNIST
adityassrana/pytorch-image-classification
A script to quickly evaluate image classification performance on different architectures, optimizers and datasetss
adityassrana/MCV-M5-VR
Detectron2 implementations of object detection and instance segmentation on KITTI, KITTI-MOTS and MOTS Challenge datasets. Extensively experimented with different Faster-RCNN, RetinaNet and Mask-RCNN architectures available in the Model Zoo.
adityassrana/MCV-M6-VA
Weekly progress made on the task of Multi-Target Multi-Camera Tracking by implementing background modelling, object detection, IoU and Kalman tracking, block matching optical flow, video stabilization, metric learning using Siamese networks and tracklet matching algorithms.
adityassrana/mobile-compression
Efficient architectures for image compression
adityassrana/old_blog_template