research
∙
07/28/2023
SimDETR: Simplifying self-supervised pretraining for DETR
DETR-based object detectors have achieved remarkable performance but are...
share
research
∙
04/04/2023
Black Box Few-Shot Adaptation for Vision-Language models
Vision-Language (V-L) models trained with contrastive learning to align ...
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...
research
∙
10/05/2022
Variational prompt tuning improves generalization of vision-language models
Prompt tuning provides an efficient mechanism to adapt large vision-lang...
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...
research
∙
09/29/2022
REST: REtrieve Self-Train for generative action recognition
This work is on training a generative action/video recognition model who...
research
∙
08/23/2022
Efficient Attention-free Video Shift Transformers
This paper tackles the problem of efficient video recognition. In this a...
research
∙
06/16/2022
iBoot: Image-bootstrapped Self-Supervised Video Representation Learning
Learning visual representations through self-supervision is an extremely...
research
∙
05/13/2022
Knowledge Distillation Meets Open-Set Semi-Supervised Learning
Existing knowledge distillation methods mostly focus on distillation of ...
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...
research
∙
11/03/2021
Subpixel Heatmap Regression for Facial Landmark Localization
Deep Learning models based on heatmap regression have revolutionized the...
research
∙
10/26/2021
Defensive Tensorization
We propose defensive tensorization, an adversarial defence technique tha...
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...
research
∙
06/10/2021
Space-time Mixing Attention for Video Transformer
This paper is on video recognition using Transformers. Very recent attem...
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...
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...
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...
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...
research
∙
10/07/2020
High-Capacity Expert Binary Networks
Network binarization is a promising hardware-aware direction for creatin...
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...
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...
research
∙
03/09/2020
Knowledge distillation via adaptive instance normalization
This paper addresses the problem of model compression via knowledge dist...
research
∙
03/03/2020
BATS: Binary ArchitecTure Search
This paper proposes Binary ArchitecTure Search (BATS), a framework that ...
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...
research
∙
11/14/2019
Towards Pose-invariant Lip-Reading
Lip-reading models have been significantly improved recently thanks to p...
research
∙
09/30/2019
XNOR-Net++: Improved Binary Neural Networks
This paper proposes an improved training algorithm for binary neural net...
research
∙
06/14/2019
Efficient N-Dimensional Convolutions via Higher-Order Factorization
With the unprecedented success of deep convolutional neural networks cam...
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...
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...
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...
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...
research
∙
08/14/2018
Hierarchical binary CNNs for landmark localization with limited resources
Our goal is to design architectures that retain the groundbreaking perfo...
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...
research
∙
12/07/2017
Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs
This paper addresses two challenging tasks: improving the quality of rea...
research
∙
03/22/2017
Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
3D face reconstruction is a fundamental Computer Vision problem of extra...
research
∙
03/21/2017
How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)
This paper investigates how far a very deep neural network is from attai...
research
∙
03/02/2017
Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources
Our goal is to design architectures that retain the groundbreaking perfo...
research
∙
09/29/2016
Two-stage Convolutional Part Heatmap Regression for the 1st 3D Face Alignment in the Wild (3DFAW) Challenge
This paper describes our submission to the 1st 3D Face Alignment in the ...
research
∙
09/06/2016
