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09/14/2023
ALWOD: Active Learning for Weakly-Supervised Object Detection
Object detection (OD), a crucial vision task, remains challenged by the ...
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08/05/2023
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation
Semi-supervised semantic segmentation involves assigning pixel-wise labe...
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06/29/2023
Learning from Synthetic Human Group Activities
The understanding of complex human interactions and group activities has...
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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...
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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...
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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...
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10/26/2022
Visual Semantic Parsing: From Images to Abstract Meaning Representation
The success of scene graphs for visual scene understanding has brought a...
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07/03/2022
NP-Match: When Neural Processes meet Semi-Supervised Learning
Semi-supervised learning (SSL) has been widely explored in recent years,...
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06/18/2022
SAViR-T: Spatially Attentive Visual Reasoning with Transformers
We present a novel computational model, "SAViR-T", for the family of vis...
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03/24/2022
HMFS: Hybrid Masking for Few-Shot Segmentation
We study few-shot semantic segmentation that aims to segment a target ob...
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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...
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10/22/2021
Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN
Multi-attribute conditional image generation is a challenging problem in...
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09/27/2021
DAReN: A Collaborative Approach Towards Reasoning And Disentangling
Computational learning approaches to solving visual reasoning tests, suc...
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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...
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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...
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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...
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12/04/2020
MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANs
Multilabel conditional image generation is a challenging problem in comp...
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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...
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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 ...
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11/17/2020
Recursive Inference for Variational Autoencoders
Inference networks of traditional Variational Autoencoders (VAEs) are ty...
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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...
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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...
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02/25/2020
CookGAN: Meal Image Synthesis from Ingredients
In this work we propose a new computational framework, based on generati...
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10/13/2019
Deep Crowd-Flow Prediction in Built Environments
Predicting the behavior of crowds in complex environments is a key requi...
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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...
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09/26/2019
Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation
Domain Adaptation (DA), the process of effectively adapting task models ...
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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...
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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...
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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...
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05/16/2019
Efficient Deep Gaussian Process Models for Variable-Sized Input
Deep Gaussian processes (DGP) have appealing Bayesian properties, can ha...
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05/09/2019
The Art of Food: Meal Image Synthesis from Ingredients
In this work we propose a new computational framework, based on generati...
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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...
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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...
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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...
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10/26/2018
Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach
Unsupervised domain adaptation (uDA) models focus on pairwise adaptation...
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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 ...
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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...
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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...
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09/29/2017
Unsupervised Domain Adaptation with Copula Models
We study the task of unsupervised domain adaptation, where no labeled da...
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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...
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09/26/2016
Robust Time-Series Retrieval Using Probabilistic Adaptive Segmental Alignment
Traditional pairwise sequence alignment is based on matching individual ...
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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...
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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 ...
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07/09/2015
Intrinsic Non-stationary Covariance Function for Climate Modeling
Designing a covariance function that represents the underlying correlati...
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07/03/2015
D-MFVI: Distributed Mean Field Variational Inference using Bregman ADMM
Bayesian models provide a framework for probabilistic modelling of compl...
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06/30/2015
Gaussian Process for Noisy Inputs with Ordering Constraints
We study the Gaussian Process regression model in the context of trainin...
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06/30/2015
Discovering Characteristic Landmarks on Ancient Coins using Convolutional Networks
In this paper, we propose a novel method to find characteristic landmark...
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06/30/2015
Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation
Video segmentation is a stepping stone to understanding video context. V...
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06/30/2015
Fast ADMM Algorithm for Distributed Optimization with Adaptive Penalty
We propose new methods to speed up convergence of the Alternating Direct...
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01/23/2013
