Vladimir Pavlovic

research

∙ 09/14/2023

ALWOD: Active Learning for Weakly-Supervised Object Detection

Object detection (OD), a crucial vision task, remains challenged by the ...

0 Yuting Wang, et al. ∙

research

∙ 08/05/2023

NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation

Semi-supervised semantic segmentation involves assigning pixel-wise labe...

0 Jianfeng Wang, et al. ∙

research

∙ 06/29/2023

Learning from Synthetic Human Group Activities

The understanding of complex human interactions and group activities has...

0 Che-Jui Chang, et al. ∙

research

∙ 12/09/2022

MSI: Maximize Support-Set Information for Few-Shot Segmentation

FSS(Few-shot segmentation) aims to segment a target class with a small n...

0 Seonghyeon Moon, et al. ∙

research

∙ 12/02/2022

D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation

Weakly-supervised object detection (WSOD) models attempt to leverage ima...

16 Yuting Wang, et al. ∙

research

∙ 11/02/2022

An Information-Theoretic Approach for Estimating Scenario Generalization in Crowd Motion Prediction

Learning-based approaches to modeling crowd motion have become increasin...

0 Gang Qiao, et al. ∙

research

∙ 10/26/2022

Visual Semantic Parsing: From Images to Abstract Meaning Representation

The success of scene graphs for visual scene understanding has brought a...

0 Mohamed Ashraf Abdelsalam, et al. ∙

research

∙ 07/03/2022

NP-Match: When Neural Processes meet Semi-Supervised Learning

Semi-supervised learning (SSL) has been widely explored in recent years,...

0 Jianfeng Wang, et al. ∙

research

∙ 06/18/2022

SAViR-T: Spatially Attentive Visual Reasoning with Transformers

We present a novel computational model, "SAViR-T", for the family of vis...

27 Pritish Sahu, et al. ∙

research

∙ 03/24/2022

HMFS: Hybrid Masking for Few-Shot Segmentation

We study few-shot semantic segmentation that aims to segment a target ob...

0 Seonghyeon Moon, et al. ∙

research

∙ 01/18/2022

MUSE-VAE: Multi-Scale VAE for Environment-Aware Long Term Trajectory Prediction

Accurate long-term trajectory prediction in complex scenes, where multip...

0 Mihee Lee, et al. ∙

research

∙ 10/22/2021

Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN

Multi-attribute conditional image generation is a challenging problem in...

6 Fangda Han, et al. ∙

research

∙ 09/27/2021

DAReN: A Collaborative Approach Towards Reasoning And Disentangling

Computational learning approaches to solving visual reasoning tests, suc...

1 Pritish Sahu, et al. ∙

research

∙ 02/05/2021

Reducing the Amortization Gap in Variational Autoencoders: A Bayesian Random Function Approach

Variational autoencoder (VAE) is a very successful generative model whos...

0 Minyoung Kim, et al. ∙

research

∙ 02/04/2021

CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval

Despite the abundance of multi-modal data, such as image-text pairs, the...

7 Hai X. Pham, et al. ∙

research

∙ 12/23/2020

Private-Shared Disentangled Multimodal VAE for Learning of Hybrid Latent Representations

Multi-modal generative models represent an important family of deep mode...

9 Mihee Lee, et al. ∙

research

∙ 12/04/2020

MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANs

Multilabel conditional image generation is a challenging problem in comp...

11 Fangda Han, et al. ∙

research

∙ 12/02/2020

Cross-modal Retrieval and Synthesis (X-MRS): Closing the modality gap in shared subspace

Computational food analysis (CFA), a broad set of methods that attempt t...

0 Ricardo Guerrero, et al. ∙

research

∙ 12/01/2020

Learning Disentangled Latent Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach

We deal with the problem of learning the underlying disentangled latent ...

0 Minyoung Kim, et al. ∙

research

∙ 11/17/2020

Recursive Inference for Variational Autoencoders

Inference networks of traditional Variational Autoencoders (VAEs) are ty...

0 Minyoung Kim, et al. ∙

research

∙ 10/17/2020

Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images

Increased awareness of the impact of food consumption on health and life...

1 Jiatong Li, et al. ∙

research

∙ 09/07/2020

Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models

In deep representational learning, it is often desired to isolate a part...

3 Minyoung Kim, et al. ∙

research

∙ 02/25/2020

CookGAN: Meal Image Synthesis from Ingredients

In this work we propose a new computational framework, based on generati...

35 Fangda Han, et al. ∙

research

∙ 10/13/2019

Deep Crowd-Flow Prediction in Built Environments

Predicting the behavior of crowds in complex environments is a key requi...

14 Samuel S. Sohn, et al. ∙

research

∙ 10/02/2019

Scenario Generalization of Data-driven Imitation Models in Crowd Simulation

Crowd simulation, the study of the movement of multiple agents in comple...

1 Gang Qiao, et al. ∙

research

∙ 09/26/2019

Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation

Domain Adaptation (DA), the process of effectively adapting task models ...

11 Behnam Gholami, et al. ∙

research

∙ 09/26/2019

Deep Cooking: Predicting Relative Food Ingredient Amounts from Images

In this paper, we study the novel problem of not only predicting ingredi...

34 Jiatong Li, et al. ∙

research

∙ 09/26/2019

Fast and Effective Adaptation of Facial Action Unit Detection Deep Model

Detecting facial action units (AU) is one of the fundamental steps in au...

4 Mihee Lee, et al. ∙

research

∙ 09/06/2019

Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement

We propose a family of novel hierarchical Bayesian deep auto-encoder mod...

17 Minyoung Kim, et al. ∙

research

∙ 05/16/2019

Efficient Deep Gaussian Process Models for Variable-Sized Input

Deep Gaussian processes (DGP) have appealing Bayesian properties, can ha...

5 Issam H. Laradji, et al. ∙

research

∙ 05/09/2019

The Art of Food: Meal Image Synthesis from Ingredients

In this work we propose a new computational framework, based on generati...

1 Fangda Han, et al. ∙

research

∙ 05/06/2019

Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

In this paper, we propose a generative framework that unifies depth-base...

7 Lu Sheng, et al. ∙

research

∙ 02/23/2019

Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach

In unsupervised domain adaptation, it is widely known that the target do...

5 Minyoung Kim, et al. ∙

research

∙ 02/05/2019

Relevance Factor VAE: Learning and Identifying Disentangled Factors

We propose a novel VAE-based deep auto-encoder model that can learn dise...

11 Minyoung Kim, et al. ∙

research

∙ 10/26/2018

Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach

Unsupervised domain adaptation (uDA) models focus on pairwise adaptation...

1 Behnam Gholami, et al. ∙

research

∙ 03/21/2018

Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network

This paper presents Generative Adversarial Talking Head (GATH), a novel ...

1 Hai X. Pham, et al. ∙

research

∙ 10/10/2017

The Role of Data-driven Priors in Multi-agent Crowd Trajectory Estimation

Trajectory interpolation, the process of filling-in the gaps and removin...

1 Gang Qiao, et al. ∙

research

∙ 10/02/2017

End-to-end Learning for 3D Facial Animation from Raw Waveforms of Speech

We present a deep learning framework for real-time speech-driven 3D faci...

1 Hai X. Pham, et al. ∙

research

∙ 09/29/2017

Unsupervised Domain Adaptation with Copula Models

We study the task of unsupervised domain adaptation, where no labeled da...

1 Cuong D. Tran, et al. ∙

research

∙ 03/25/2017

Sketch-based Face Editing in Video Using Identity Deformation Transfer

We address the problem of using hand-drawn sketch to edit facial identit...

1 Long Zhao, et al. ∙

research

∙ 09/26/2016

Robust Time-Series Retrieval Using Probabilistic Adaptive Segmental Alignment

Traditional pairwise sequence alignment is based on matching individual ...

1 Shahriar Shariat, et al. ∙

research

∙ 10/13/2015

Variable-state Latent Conditional Random Fields for Facial Expression Recognition and Action Unit Detection

Automated recognition of facial expressions of emotions, and detection o...

1 Robert Walecki, et al. ∙

research

∙ 07/10/2015

Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes

We introduce a novel robust hybrid 3D face tracking framework from RGBD ...

1 Hai X. Pham, et al. ∙

research

∙ 07/09/2015

Intrinsic Non-stationary Covariance Function for Climate Modeling

Designing a covariance function that represents the underlying correlati...

1 Chintan A. Dalal, et al. ∙

research

∙ 07/03/2015

D-MFVI: Distributed Mean Field Variational Inference using Bregman ADMM

Bayesian models provide a framework for probabilistic modelling of compl...

1 Behnam Babagholami-Mohamadabadi, et al. ∙

research

∙ 06/30/2015

Gaussian Process for Noisy Inputs with Ordering Constraints

We study the Gaussian Process regression model in the context of trainin...

1 Cuong Tran, et al. ∙

research

∙ 06/30/2015

Discovering Characteristic Landmarks on Ancient Coins using Convolutional Networks

In this paper, we propose a novel method to find characteristic landmark...

1 Jongpil Kim, et al. ∙

research

∙ 06/30/2015

Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation

Video segmentation is a stepping stone to understanding video context. V...

1 Saehoon Yi, et al. ∙

research

∙ 06/30/2015

Fast ADMM Algorithm for Distributed Optimization with Adaptive Penalty

We propose new methods to speed up convergence of the Alternating Direct...

1 Changkyu Song, et al. ∙

research

∙ 01/23/2013

Variational Learning in Mixed-State Dynamic Graphical Models

Many real-valued stochastic time-series are locally linear (Gassian), bu...

1 Vladimir Pavlovic, et al. ∙

Vladimir Pavlovic

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