Georgios Tzimiropoulos

research

∙ 07/28/2023

SimDETR: Simplifying self-supervised pretraining for DETR

DETR-based object detectors have achieved remarkable performance but are...

0 Ioannis Maniadis Metaxas, et al. ∙

research

∙ 07/20/2023

HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces

In this paper, we present our method for neural face reenactment, called...

0 Stella Bounareli, et al. ∙

research

∙ 04/04/2023

Black Box Few-Shot Adaptation for Vision-Language models

Vision-Language (V-L) models trained with contrastive learning to align ...

0 Yassine Ouali, et al. ∙

research

∙ 04/03/2023

DivClust: Controlling Diversity in Deep Clustering

Clustering has been a major research topic in the field of machine learn...

0 Ioannis Maniadis Metaxas, et al. ∙

research

∙ 11/30/2022

Part-based Face Recognition with Vision Transformers

Holistic methods using CNNs and margin-based losses have dominated resea...

0 Zhonglin Sun, et al. ∙

research

∙ 10/10/2022

FS-DETR: Few-Shot DEtection TRansformer with prompting and without re-training

This paper is on Few-Shot Object Detection (FSOD), where given a few tem...

14 Adrian Bulat, et al. ∙

research

∙ 10/05/2022

Variational prompt tuning improves generalization of vision-language models

Prompt tuning provides an efficient mechanism to adapt large vision-lang...

3 Mohammad Mahdi Derakhshani, et al. ∙

research

∙ 10/03/2022

Language-Aware Soft Prompting for Vision Language Foundation Models

This paper is on soft prompt learning for Vision & Language (V L) mode...

0 Adrian Bulat, et al. ∙

research

∙ 09/29/2022

REST: REtrieve Self-Train for generative action recognition

This work is on training a generative action/video recognition model who...

0 Adrian Bulat, et al. ∙

research

∙ 09/27/2022

StyleMask: Disentangling the Style Space of StyleGAN2 for Neural Face Reenactment

In this paper we address the problem of neural face reenactment, where, ...

26 Stella Bounareli, et al. ∙

research

∙ 08/23/2022

Efficient Attention-free Video Shift Transformers

This paper tackles the problem of efficient video recognition. In this a...

0 Adrian Bulat, et al. ∙

research

∙ 06/16/2022

iBoot: Image-bootstrapped Self-Supervised Video Representation Learning

Learning visual representations through self-supervision is an extremely...

0 Fatemeh Saleh, et al. ∙

research

∙ 06/05/2022

ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences

This work addresses the problem of discovering non-linear interpretable ...

0 Christos Tzelepis, et al. ∙

research

∙ 05/31/2022

From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discovery

This paper proposes a novel paradigm for the unsupervised learning of ob...

0 Dimitrios Mallis, et al. ∙

research

∙ 05/13/2022

Knowledge Distillation Meets Open-Set Semi-Supervised Learning

Existing knowledge distillation methods mostly focus on distillation of ...

13 Jing Yang, et al. ∙

research

∙ 05/06/2022

EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers

Self-attention based models such as vision transformers (ViTs) have emer...

18 Junting Pan, et al. ∙

research

∙ 01/31/2022

Finding Directions in GAN's Latent Space for Neural Face Reenactment

This paper is on face/head reenactment where the goal is to transfer the...

0 Stella Bounareli, et al. ∙

research

∙ 11/22/2021

S3: Supervised Self-supervised Learning under Label Noise

Despite the large progress in supervised learning with Neural Networks, ...

0 Chen Feng, et al. ∙

research

∙ 11/03/2021

Subpixel Heatmap Regression for Facial Landmark Localization

Deep Learning models based on heatmap regression have revolutionized the...

0 Adrian Bulat, et al. ∙

research

∙ 10/26/2021

Defensive Tensorization

We propose defensive tensorization, an adversarial defence technique tha...

4 Adrian Bulat, et al. ∙

research

∙ 10/06/2021

SAIC_Cambridge-HuPBA-FBK Submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021

This report presents the technical details of our submission to the EPIC...

0 Swathikiran Sudhakaran, et al. ∙

research

∙ 09/27/2021

WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

This work addresses the problem of discovering, in an unsupervised manne...

13 Christos Tzelepis, et al. ∙

research

∙ 06/10/2021

Space-time Mixing Attention for Video Transformer

This paper is on video recognition using Transformers. Very recent attem...

0 Adrian Bulat, et al. ∙

research

∙ 03/31/2021

Bit-Mixer: Mixed-precision networks with runtime bit-width selection

Mixed-precision networks allow for a variable bit-width quantization for...

0 Adrian Bulat, et al. ∙

research

∙ 03/30/2021

Pre-training strategies and datasets for facial representation learning

What is the best way to learn a universal face representation? Recent wo...

0 Adrian Bulat, et al. ∙

research

∙ 03/24/2021

Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition

Temporal context is key to the recognition of expressions of emotion. Ex...

0 Enrique Sanchez, et al. ∙

research

∙ 02/08/2021

Improving memory banks for unsupervised learning with large mini-batch, consistency and hard negative mining

An important component of unsupervised learning by instance-based discri...

0 Adrian Bulat, et al. ∙

research

∙ 11/03/2020

Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning

This paper tackles the challenging problem of estimating the intensity o...

0 Enrique Sanchez, et al. ∙

research

∙ 10/07/2020

High-Capacity Expert Binary Networks

Network binarization is a promising hardware-aware direction for creatin...

0 Adrian Bulat, et al. ∙

research

∙ 04/14/2020

A Transfer Learning approach to Heatmap Regression for Action Unit intensity estimation

Action Units (AUs) are geometrically-based atomic facial muscle movement...

12 Ioanna Ntinou, et al. ∙

research

∙ 03/25/2020

Training Binary Neural Networks with Real-to-Binary Convolutions

This paper shows how to train binary networks to within a few percent po...

9 Brais Martinez, et al. ∙

research

∙ 03/09/2020

Knowledge distillation via adaptive instance normalization

This paper addresses the problem of model compression via knowledge dist...

17 Jing Yang, et al. ∙

research

∙ 03/03/2020

BATS: Binary ArchitecTure Search

This paper proposes Binary ArchitecTure Search (BATS), a framework that ...

31 Adrian Bulat, et al. ∙

research

∙ 02/25/2020

Toward fast and accurate human pose estimation via soft-gated skip connections

This paper is on highly accurate and highly efficient human pose estimat...

0 Adrian Bulat, et al. ∙

research

∙ 11/14/2019

Towards Pose-invariant Lip-Reading

Lip-reading models have been significantly improved recently thanks to p...

19 Shiyang Cheng, et al. ∙

research

∙ 10/21/2019

Object landmark discovery through unsupervised adaptation

This paper proposes a method to ease the unsupervised learning of object...

15 Enrique Sanchez, et al. ∙

research

∙ 09/30/2019

XNOR-Net++: Improved Binary Neural Networks

This paper proposes an improved training algorithm for binary neural net...

0 Adrian Bulat, et al. ∙

research

∙ 09/11/2019

AnimalWeb: A Large-Scale Hierarchical Dataset of Annotated Animal Faces

Being heavily reliant on animals, it is our ethical obligation to improv...

7 Muhammad Haris Khan, et al. ∙

research

∙ 04/16/2019

Matrix and tensor decompositions for training binary neural networks

This paper is on improving the training of binary neural networks in whi...

6 Adrian Bulat, et al. ∙

research

∙ 04/12/2019

Incremental multi-domain learning with network latent tensor factorization

The prominence of deep learning, large amount of annotated data and incr...

8 Adrian Bulat, et al. ∙

research

∙ 04/11/2019

Improved training of binary networks for human pose estimation and image recognition

Big neural networks trained on large datasets have advanced the state-of...

4 Adrian Bulat, et al. ∙

research

∙ 04/04/2019

T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor

Recent findings indicate that over-parametrization, while crucial for su...

16 Jean Kossaifi, et al. ∙

research

∙ 12/12/2018

Features Extraction Based on an Origami Representation of 3D Landmarks

Feature extraction analysis has been widely investigated during the last...

0 Juan Manuel Fernández Montenegro, et al. ∙

research

∙ 12/06/2018

Learning to Infer the Depth Map of a Hand from its Color Image

We propose the first approach to the problem of inferring the depth map ...

0 Vassilis C. Nicodemou, et al. ∙

research

∙ 11/03/2018

Pushing the boundaries of audiovisual word recognition using Residual Networks and LSTMs

Visual and audiovisual speech recognition are witnessing a renaissance w...

0 Themos Stafylakis, et al. ∙

research

∙ 09/28/2018

Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture

Recent works in speech recognition rely either on connectionist temporal...

0 Stavros Petridis, et al. ∙

research

∙ 09/11/2018

3D Human Body Reconstruction from a Single Image via Volumetric Regression

This paper proposes the use of an end-to-end Convolutional Neural Networ...

2 Aaron S. Jackson, et al. ∙

research

∙ 08/14/2018

Hierarchical binary CNNs for landmark localization with limited resources

Our goal is to design architectures that retain the groundbreaking perfo...

8 Adrian Bulat, et al. ∙

research

∙ 07/30/2018

To learn image super-resolution, use a GAN to learn how to do image degradation first

This paper is on image and face super-resolution. The vast majority of p...

6 Adrian Bulat, et al. ∙

research

∙ 07/23/2018

Zero-shot keyword spotting for visual speech recognition in-the-wild

Visual keyword spotting (KWS) is the problem of estimating whether a tex...

2 Themos Stafylakis, et al. ∙

Georgios Tzimiropoulos

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