2 citations · 3 across the 3 of their papers we have counts for
6 papers
Self-Denoising Neural Networks for Few Shot Learning
Steven Schwarcz, Sai Saketh Rambhatla, Rama Chellappa
In this paper, we introduce a new architecture for few shot learning, the task of teaching a neural network from as few as one or five labeled examples. Inspired by the theoretical…
To Boost or not to Boost: On the Limits of Boosted Neural Networks
Sai Saketh Rambhatla, Michael Jones, Rama Chellappa
Boosting is a method for finding a highly accurate hypothesis by linearly combining many ``weak" hypotheses, each of which may be only moderately accurate. Thus, boosting is a meth…
The Pursuit of Knowledge: Discovering and Localizing Novel Categories using Dual Memory
Sai Saketh Rambhatla, Rama Chellappa, Abhinav Shrivastava
We tackle object category discovery, which is the problem of discovering and localizing novel objects in a large unlabeled dataset. While existing methods show results on datasets…
Spatial Priming for Detecting Human-Object Interactions
Ankan Bansal, Sai Saketh Rambhatla, Abhinav Shrivastava +1
The relative spatial layout of a human and an object is an important cue for determining how they interact. However, until now, spatial layout has been used just as side-informatio…
A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification
Pirazh Khorramshahi, Amit Kumar, Neehar Peri +3
In recent years, attention models have been extensively used for person and vehicle re-identification. Most re-identification methods are designed to focus attention on key-point l…
Detecting Human-Object Interactions via Functional Generalization
Ankan Bansal, Sai Saketh Rambhatla, Abhinav Shrivastava +1
We present an approach for detecting human-object interactions (HOIs) in images, based on the idea that humans interact with functionally similar objects in a similar manner. The p…