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07/28/2023
SimDETR: Simplifying self-supervised pretraining for DETR
DETR-based object detectors have achieved remarkable performance but are...
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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...
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04/04/2023
Black Box Few-Shot Adaptation for Vision-Language models
Vision-Language (V-L) models trained with contrastive learning to align ...
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04/03/2023
DivClust: Controlling Diversity in Deep Clustering
Clustering has been a major research topic in the field of machine learn...
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11/30/2022
Part-based Face Recognition with Vision Transformers
Holistic methods using CNNs and margin-based losses have dominated resea...
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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...
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10/05/2022
Variational prompt tuning improves generalization of vision-language models
Prompt tuning provides an efficient mechanism to adapt large vision-lang...
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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...
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09/29/2022
REST: REtrieve Self-Train for generative action recognition
This work is on training a generative action/video recognition model who...
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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, ...
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08/23/2022
Efficient Attention-free Video Shift Transformers
This paper tackles the problem of efficient video recognition. In this a...
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06/16/2022
iBoot: Image-bootstrapped Self-Supervised Video Representation Learning
Learning visual representations through self-supervision is an extremely...
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06/05/2022
ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences
This work addresses the problem of discovering non-linear interpretable ...
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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...
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05/13/2022
Knowledge Distillation Meets Open-Set Semi-Supervised Learning
Existing knowledge distillation methods mostly focus on distillation of ...
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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...
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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...
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11/22/2021
S3: Supervised Self-supervised Learning under Label Noise
Despite the large progress in supervised learning with Neural Networks, ...
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11/03/2021
Subpixel Heatmap Regression for Facial Landmark Localization
Deep Learning models based on heatmap regression have revolutionized the...
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10/26/2021
Defensive Tensorization
We propose defensive tensorization, an adversarial defence technique tha...
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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...
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09/27/2021
WarpedGANSpace: Finding non-linear RBF paths in GAN latent space
This work addresses the problem of discovering, in an unsupervised manne...
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06/10/2021
Space-time Mixing Attention for Video Transformer
This paper is on video recognition using Transformers. Very recent attem...
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03/31/2021
Bit-Mixer: Mixed-precision networks with runtime bit-width selection
Mixed-precision networks allow for a variable bit-width quantization for...
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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...
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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...
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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...
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11/03/2020
Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning
This paper tackles the challenging problem of estimating the intensity o...
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10/07/2020
High-Capacity Expert Binary Networks
Network binarization is a promising hardware-aware direction for creatin...
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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...
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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...
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03/09/2020
Knowledge distillation via adaptive instance normalization
This paper addresses the problem of model compression via knowledge dist...
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03/03/2020
BATS: Binary ArchitecTure Search
This paper proposes Binary ArchitecTure Search (BATS), a framework that ...
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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...
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11/14/2019
Towards Pose-invariant Lip-Reading
Lip-reading models have been significantly improved recently thanks to p...
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10/21/2019
Object landmark discovery through unsupervised adaptation
This paper proposes a method to ease the unsupervised learning of object...
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09/30/2019
XNOR-Net++: Improved Binary Neural Networks
This paper proposes an improved training algorithm for binary neural net...
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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...
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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...
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04/12/2019
Incremental multi-domain learning with network latent tensor factorization
The prominence of deep learning, large amount of annotated data and incr...
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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...
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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...
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12/12/2018
Features Extraction Based on an Origami Representation of 3D Landmarks
Feature extraction analysis has been widely investigated during the last...
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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 ...
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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...
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09/28/2018
Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture
Recent works in speech recognition rely either on connectionist temporal...
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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...
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08/14/2018
Hierarchical binary CNNs for landmark localization with limited resources
Our goal is to design architectures that retain the groundbreaking perfo...
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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...
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07/23/2018
