Search Results for author: Shikhar Sharma

Found 11 papers, 3 papers with code

MS-nowcasting: Operational Precipitation Nowcasting with Convolutional LSTMs at Microsoft Weather

no code implementations18 Nov 2021 Sylwester Klocek, Haiyu Dong, Matthew Dixon, Panashe Kanengoni, Najeeb Kazmi, Pete Luferenko, Zhongjian Lv, Shikhar Sharma, Jonathan Weyn, Siqi Xiang

We present the encoder-forecaster convolutional long short-term memory (LSTM) deep-learning model that powers Microsoft Weather's operational precipitation nowcasting product.

Optical Flow Estimation

Object-Centric Image Generation from Layouts

no code implementations16 Mar 2020 Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma

In this paper, we start with the idea that a model must be able to understand individual objects and relationships between objects in order to generate complex scenes well.

Layout-to-Image Generation

From FiLM to Video: Multi-turn Question Answering with Multi-modal Context

no code implementations17 Dec 2018 Dat Tien Nguyen, Shikhar Sharma, Hannes Schulz, Layla El Asri

Understanding audio-visual content and the ability to have an informative conversation about it have both been challenging areas for intelligent systems.

Question Answering

ChatPainter: Improving Text to Image Generation using Dialogue

no code implementations22 Feb 2018 Shikhar Sharma, Dendi Suhubdy, Vincent Michalski, Samira Ebrahimi Kahou, Yoshua Bengio

Synthesizing realistic images from text descriptions on a dataset like Microsoft Common Objects in Context (MS COCO), where each image can contain several objects, is a challenging task.

Ranked #20 on Text-to-Image Generation on COCO (Inception score metric)

Text to image generation Text-to-Image Generation

Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation

3 code implementations ICLR 2018 Shikhar Sharma, Layla El Asri, Hannes Schulz, Jeremie Zumer

However, previous work in dialogue response generation has shown that these metrics do not correlate strongly with human judgment in the non task-oriented dialogue setting.

Dialogue Generation Machine Translation +2

Learning Preferences for Manipulation Tasks from Online Coactive Feedback

no code implementations5 Jan 2016 Ashesh Jain, Shikhar Sharma, Thorsten Joachims, Ashutosh Saxena

We consider the problem of learning preferences over trajectories for mobile manipulators such as personal robots and assembly line robots.

online learning

Cannot find the paper you are looking for? You can Submit a new open access paper.