activity
20182021
most citedWhat-If Motion Prediction for Autonomous Driving

23 citations · 23 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Segmentation-grounded Scene Graph Generation

Siddhesh Khandelwal, Mohammed Suhail, Leonid Sigal

Scene graph generation has emerged as an important problem in computer vision. While scene graphs provide a grounded representation of objects, their locations and relations in an…

cs.LG202023 cited

What-If Motion Prediction for Autonomous Driving

Siddhesh Khandelwal, William Qi, Jagjeet Singh +2

Forecasting the long-term future motion of road actors is a core challenge to the deployment of safe autonomous vehicles (AVs). Viable solutions must account for both the static ge…

cs.CV2020

UniT: Unified Knowledge Transfer for Any-shot Object Detection and Segmentation

Siddhesh Khandelwal, Raghav Goyal, Leonid Sigal

Methods for object detection and segmentation rely on large scale instance-level annotations for training, which are difficult and time-consuming to collect. Efforts to alleviate t…

cs.CV2019

AttentionRNN: A Structured Spatial Attention Mechanism

Siddhesh Khandelwal, Leonid Sigal

Visual attention mechanisms have proven to be integrally important constituent components of many modern deep neural architectures. They provide an efficient and effective way to u…

cs.CL2018

Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention

Sharmistha Jat, Siddhesh Khandelwal, Partha Talukdar

Relation extraction is the problem of classifying the relationship between two entities in a given sentence. Distant Supervision (DS) is a popular technique for developing relation…