PRedItOR: Text Guided Image Editing with Diffusion Prior

Diffusion models have shown remarkable capabilities in generating high quality and creative images conditioned on text. An interesting application of such models is structure preserving text guided image editing. Existing approaches rely on text conditioned diffusion models such as Stable Diffusion or Imagen and require compute intensive optimization of text embeddings or fine-tuning the model weights for text guided image editing. We explore text guided image editing with a Hybrid Diffusion Model (HDM) architecture similar to DALLE-2. Our architecture consists of a diffusion prior model that generates CLIP image embedding conditioned on a text prompt and a custom Latent Diffusion Model trained to generate images conditioned on CLIP image embedding. We discover that the diffusion prior model can be used to perform text guided conceptual edits on the CLIP image embedding space without any finetuning or optimization. We combine this with structure preserving edits on the image decoder using existing approaches such as reverse DDIM to perform text guided image editing. Our approach, PRedItOR does not require additional inputs, fine-tuning, optimization or objectives and shows on par or better results than baselines qualitatively and quantitatively. We provide further analysis and understanding of the diffusion prior model and believe this opens up new possibilities in diffusion models research

Visual Search at eBay

In this paper, we propose a novel end-to-end approach for scalable visual search infrastructure. We discuss the challenges we faced for a massive volatile inventory like at eBay and present our solution to overcome those. We harness the availability of large image collection of eBay listings and state-of-the-art deep learning techniques to perform visual search at scale. Supervised approach for optimized search limited to top predicted categories and also for compact binary signature are key to scale up without compromising accuracy and precision. Both use a common deep neural network requiring only a single forward inference. The system architecture is presented with in-depth discussions of its basic components and optimizations for a trade-off between search relevance and latency. This solution is currently deployed in a distributed cloud infrastructure and fuels visual search in eBay ShopBot and Close5. We show benchmark on ImageNet dataset on which our approach is faster and more accurate than several unsupervised baselines. We share our learnings with the hope that visual search becomes a first class citizen for all large scale search engines rather than an afterthought.Comment: To appear in 23rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017. A demonstration video can be found at https://youtu.be/iYtjs32vh4

A crusade against scorpion sting: Life and works of Dr. Himmatrao Bawaskar

In the times of rapid advancement of science and technology, advance medical equipment and hi tech hospitals represent the face of medical science. The aspirations and ambitions of medical professionals are also shifting, with growing concerns of deterioration of doctor patient relationship as well as disconnect between services and the community needs. The life of Dr Himmatrao Bawaskar defies several conventions of today′s medical practice. His outstanding dedication towards patients and commitment to provide high quality care in resource poor setting makes him an ideal role model for younger generation of physicians in India

Process thermoneutral point in dry autothermal reforming for CO2 utilization

Dry autothermal reforming is a novel CO2 utilization process. Thermoneutral points are considered to be the best operating points in autothermal reforming reactors. A theoretical study was done to determine the process thermoneutral points for complete dry autothermal reforming process considering the basic preheater, reactor and condenser configuration. The results were compared to the product yields at reactor thermoneutral points for the same input feed and temperature conditions. The process thermoneutral points were found be better for operational reasons than reactor thermoneutral points. Dry autothermal reforming of methane was used as model example in this study. This study can be used for different autothermal processes to calculate the optimum conditions at which the process can be operated in heat integrated loop without the need of any external thermal energ