14 citations · 27 across the 16 of their papers we have counts for
16 papers
Hierarchical Image Tokenization for Multi-Scale Image Super Resolution
Isma Hadji, Enrique Sanchez, Adrian Bulat +2
We introduce a multi-scale Image Super Resolution (ISR) method building on recent advances in Visual Auto-Regressive (VAR) modeling. VAR models break image tokenization into additi…
Restore, Assess, Repeat: A Unified Framework for Iterative Image Restoration
I-Hsiang Chen, Isma Hadji, Enrique Sanchez +5
Image restoration aims to recover high quality images from inputs degraded by various factors, such as adverse weather, blur, or low light. While recent studies have shown remarkab…
Multi-scale Image Super Resolution with a Single Auto-Regressive Model
Enrique Sanchez, Isma Hadji, Adrian Bulat +3
In this paper we tackle Image Super Resolution (ISR), using recent advances in Visual Auto-Regressive (VAR) modeling. VAR iteratively estimates the residual in latent space between…
MeMSVD: Long-Range Temporal Structure Capturing Using Incremental SVD
Ioanna Ntinou, Enrique Sanchez, Georgios Tzimiropoulos
This paper is on long-term video understanding where the goal is to recognise human actions over long temporal windows (up to minutes long). In prior work, long temporal context is…
Multiscale Vision Transformers meet Bipartite Matching for efficient single-stage Action Localization
Ioanna Ntinou, Enrique Sanchez, Georgios Tzimiropoulos
Action Localization is a challenging problem that combines detection and recognition tasks, which are often addressed separately. State-of-the-art methods rely on off-the-shelf bou…
Bayesian Prompt Learning for Image-Language Model Generalization
Mohammad Mahdi Derakhshani, Enrique Sanchez, Adrian Bulat +4
Foundational image-language models have generated considerable interest due to their efficient adaptation to downstream tasks by prompt learning. Prompt learning treats part of the…
REST: REtrieve & Self-Train for generative action recognition
Adrian Bulat, Enrique Sanchez, Brais Martinez +1
This work is on training a generative action/video recognition model whose output is a free-form action-specific caption describing the video (rather than an action class label). A…
From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discovery
Dimitrios Mallis, Enrique Sanchez, Matt Bell +1
This paper proposes a novel paradigm for the unsupervised learning of object landmark detectors. Contrary to existing methods that build on auxiliary tasks such as image generation…
Subpixel Heatmap Regression for Facial Landmark Localization
Adrian Bulat, Enrique Sanchez, Georgios Tzimiropoulos
Deep Learning models based on heatmap regression have revolutionized the task of facial landmark localization with existing models working robustly under large poses, non-uniform i…
Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition
Enrique Sanchez, Mani Kumar Tellamekala, Michel Valstar +1
Temporal context is key to the recognition of expressions of emotion. Existing methods, that rely on recurrent or self-attention models to enforce temporal consistency, work on the…
Pre-training strategies and datasets for facial representation learning
Adrian Bulat, Shiyang Cheng, Jing Yang +3
What is the best way to learn a universal face representation? Recent work on Deep Learning in the area of face analysis has focused on supervised learning for specific tasks of in…
Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning
Enrique Sanchez, Adrian Bulat, Anestis Zaganidis +1
This paper tackles the challenging problem of estimating the intensity of Facial Action Units with few labeled images. Contrary to previous works, our method does not require to ma…
A recurrent cycle consistency loss for progressive face-to-face synthesis
Enrique Sanchez, Michel Valstar
This paper addresses a major flaw of the cycle consistency loss when used to preserve the input appearance in the face-to-face synthesis domain. In particular, we show that the ima…
A Transfer Learning approach to Heatmap Regression for Action Unit intensity estimation
Ioanna Ntinou, Enrique Sanchez, Adrian Bulat +2
Action Units (AUs) are geometrically-based atomic facial muscle movements known to produce appearance changes at specific facial locations. Motivated by this observation we propose…
Object landmark discovery through unsupervised adaptation
Enrique Sanchez, Georgios Tzimiropoulos
This paper proposes a method to ease the unsupervised learning of object landmark detectors. Similarly to previous methods, our approach is fully unsupervised in a sense that it do…
Triple consistency loss for pairing distributions in GAN-based face synthesis
Enrique Sanchez, Michel Valstar
Generative Adversarial Networks have shown impressive results for the task of object translation, including face-to-face translation. A key component behind the success of recent a…