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Sequence Analysis and Modeling Lab

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Day: September 22, 2019

Posted on September 22, 2019October 23, 2019

Deep Cooking: Predicting Relative Food Ingredient Amounts from Images

This is a joint work by Jiatong Li, Ricardo Guerrero and Vladimir Pavlovic. The paper is accepted by the 5th International Workshop on Multimedia Assisted Dietary Management (MADiMa), ACM International Conference on Multimedia (ACMMM2019).

Abstract

In this paper, we study … Read the rest

Posted on September 22, 2019October 2, 2019

Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation

This is a joint work by Behnam Gholami, Pritish Sahu, Minyoung Kim, Vladimir Pavlovic

Our new paper on Domain Adaptation was accepted in Multi-Discipline Approach for Learning Concepts – Zero-Shot, One-Shot, Few-Shot, and Beyond and Beyond Workshop in conjunction with ICCV 2019.

Abstract

… Read the rest
Posted on September 22, 2019October 2, 2019

Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach

This is a joint work by Behnam Gholami, Pritish Sahu, Ognjen Rudovic, Konstantinos Bousmalis, Vladimir Pavlovic

Abstract

Unsupervised domain adaptation (uDA) models focus on pairwise adaptation settings where there is a single, labeled, source and a single target domain. However, in many real-world settings … Read the rest

Posted on September 22, 2019October 7, 2019

Fast Adaptation of Deep Models for Facial Action Unit Detection Using Model-Agnostic Meta-Learning

Mihee Lee, Ognjen (Oggi) Rudovic, Vladimir Pavlovic, and Maja Pantic

Abstract

Detecting facial action units (AU) is one of the fundamental steps in automatic recognition of facial expression of emotions and cognitive states. Though there have been a variety of … Read the rest

Recent Posts

  • Spring 2022 – CS536 – Machine Learning
  • Fall 2021 Courses – CS535 Pattern Recognition
  • “These Pizzas Do Not Exist”
  • Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images
  • New NSF Grant: Learning Joint Crowd-Space Embeddings for Cross-Modal Crowd Behavior Prediction

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    SEQAM Lab
    CBIM Center
    Rutgers University
    617 Bowser Road
    Piscataway, New Jersey 08854
    United States of America
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