Technical overview of Image Synthesis : Stable Diffusion

by Ankit Sachan • March 2, 2023

Tex  to Image models like DALL-E, Imagen, and Stable Diffusion have attracted a lot of attention to Image Synthesis models, recently. These models can generate impressive looking images from benign looking prompts. Here are a few typical examples of images from Stable Diffusion:                 Looking under the hood […]

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MOTR: End-to-End Multi-Object Tracking with Transformers

by Ankit Sachan • January 15, 2023

MOTR is a state of the art end-to-end multiple object tracker that does not require any temporal association between objects of adjacent frames. It directly outputs the track of objects in a sequence of input images (video). MOTR uses Deformable DETR for object detection on a single image. To understand the architecture of MOTR it […]

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GhostNetV2: Enhance Cheap Operation with Long-Range Attention

by Ankit Sachan • November 15, 2022

GhostNetV2 is a recent SOTA architecture that allows an implementation of Long-Range attention in the deep CNN frameworks used in various ML tasks such as image classification, object detection, and video analysis. GhostNetV2 proposes a new attention mechanism called DFC attention to capture long range spatial information. And it does so while keeping the implementation […]

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Understanding CLIP by OpenAI

by Ankit Sachan • May 10, 2022

CLIP By OPEN-AI Introduction Nearly all state-of-the-art visual perception algorithms rely on the same formula:  (1) pretrain a convolutional network on a large, manually annotated image classification dataset (2) finetune the network on a smaller, task-specific dataset. This technique has been widely used for several years and has led to impressive improvements on numerous tasks.  […]

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Using Active Learning to Improve your Machine Learning Models

by Ankit Sachan • April 10, 2022

Machine Learning Reality Check In the Machine Learning World or broadly in the AI Universe, the colonists such as Data Scientists, Machine Learning Engineers, Deep Learning Specialist are coached towards a belief i.e. “More Training Data Means Highly Accurate Production Model“. Which to some extent is unavoidably true but predominately it’s also a fact, that […]

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