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Ahmad Humayun

5 accepted papers

2024

DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors

NeurIPS 2024poster

Learning from previously collected data via behavioral cloning or offline reinforcement learning (RL) is a powerful recipe for scaling generalist agents by avoiding the need for expensive online learning. Despite strong generalization in some respects, agents are often remarkably brittle to minor vi…

2023

Low-shot Object Learning with Mutual Exclusivity Bias

NeurIPS 2023poster

This paper introduces Low-shot Object Learning with Mutual Exclusivity Bias (LSME), the first computational framing of mutual exclusivity bias, a phenomenon commonly observed in infants during word learning. We provide a novel dataset, comprehensive baselines, and a SOTA method to enable the ML comm…

2019

Incremental Object Learning From Contiguous Views

CVPR 2019oral

In this work, we present CRIB (Continual Recognition Inspired by Babies), a synthetic incremental object learning environment that can produce data that models visual imagery produced by object exploration in early infancy. CRIB is coupled with a new 3D object dataset, Toys-200, that contains 200 un…

Cited by 53PDFScholar
2015

The Middle Child Problem: Revisiting Parametric Min-Cut and Seeds for Object Proposals

ICCV 2015poster

Object proposals have recently fueled the progress in detection performance. These proposals aim to provide category-agnostic localizations for all objects in an image. One way to generate proposals is to perform parametric min-cuts over seed locations. This paper demonstrates that standard parametr…

Cited by 31PDFScholar