research
∙
09/01/2023
Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering
Domain adaptation (DA) aims to alleviate the domain shift between source...
share
research
∙
07/13/2022
SlimSeg: Slimmable Semantic Segmentation with Boundary Supervision
Accurate semantic segmentation models typically require significant comp...
research
∙
06/16/2022
PeQuENet: Perceptual Quality Enhancement of Compressed Video with Adaptation- and Attention-based Network
In this paper we propose a generative adversarial network (GAN) framewor...
research
∙
05/13/2022
Slimmable Video Codec
Neural video compression has emerged as a novel paradigm combining train...
research
∙
01/25/2022
Main Product Detection with Graph Networks for Fashion
Computer vision has established a foothold in the online fashion retail ...
research
∙
01/22/2022
DCNGAN: A Deformable Convolutional-Based GAN with QP Adaptation for Perceptual Quality Enhancement of Compressed Video
In this paper, we propose a deformable convolution-based generative adve...
research
∙
11/25/2021
A Novel Framework for Image-to-image Translation and Image Compression
Data-driven paradigms using machine learning are becoming ubiquitous in ...
research
∙
11/09/2021
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition
Most meta-learning approaches assume the existence of a very large set o...
research
∙
10/21/2021
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification
Human beings learn and accumulate hierarchical knowledge over their life...
research
∙
10/08/2021
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation
Domain adaptation (DA) aims to alleviate the domain shift between source...
research
∙
09/24/2021
Spatial Information Refinement for Chroma Intra Prediction in Video Coding
Video compression benefits from advanced chroma intra prediction methods...
research
∙
09/22/2021
DVC-P: Deep Video Compression with Perceptual Optimizations
Recent years have witnessed the significant development of learning-base...
research
∙
08/03/2021
Generalized Source-free Domain Adaptation
Domain adaptation (DA) aims to transfer the knowledge learned from a sou...
research
∙
05/18/2021
ACAE-REMIND for Online Continual Learning with Compressed Feature Replay
Online continual learning aims to learn from a non-IID stream of data fr...
research
∙
04/28/2021
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains
GANs largely increases the potential impact of generative models. Theref...
research
∙
04/19/2021
DANICE: Domain adaptation without forgetting in neural image compression
Neural image compression (NIC) is a new coding paradigm where coding cap...
research
∙
04/14/2021
Continual learning in cross-modal retrieval
Multimodal representations and continual learning are two areas closely ...
research
∙
03/29/2021
Slimmable Compressive Autoencoders for Practical Neural Image Compression
Neural image compression leverages deep neural networks to outperform tr...
research
∙
03/08/2021
On Implicit Attribute Localization for Generalized Zero-Shot Learning
Zero-shot learning (ZSL) aims to discriminate images from unseen classes...
research
∙
10/23/2020
Unsupervised Domain Adaptation without Source Data by Casting a BAIT
Unsupervised domain adaptation (UDA) aims to transfer the knowledge lear...
research
∙
06/26/2020
Bookworm continual learning: beyond zero-shot learning and continual learning
We propose bookworm continual learning(BCL), a flexible setting where un...
research
∙
06/10/2020
Simple and effective localized attribute representations for zero-shot learning
Zero-shot learning (ZSL) aims to discriminate images from unseen classes...
research
∙
04/22/2020
Distributed Learning and Inference with Compressed Images
Modern computer vision requires processing large amounts of data, both w...
research
∙
04/20/2020
Generative Feature Replay For Class-Incremental Learning
Humans are capable of learning new tasks without forgetting previous one...
research
∙
04/01/2020
Semantic Drift Compensation for Class-Incremental Learning
Class-incremental learning of deep networks sequentially increases the n...
research
∙
12/11/2019
Variable Rate Deep Image Compression with Modulated Autoencoder
Variable rate is a requirement for flexible and adaptable image and vide...
research
∙
12/11/2019
MineGAN: effective knowledge transfer from GANs to target domains with few images
One of the attractive characteristics of deep neural networks is their a...
research
∙
08/19/2019
SDIT: Scalable and Diverse Cross-domain Image Translation
Recently, image-to-image translation research has witnessed remarkable p...
research
∙
07/23/2019
Controlling biases and diversity in diverse image-to-image translation
The task of unpaired image-to-image translation is highly challenging du...
research
∙
07/11/2019
Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition
In recent years, convolutional neural networks (CNNs) have achieved impr...
research
∙
03/08/2019
Mix and match networks: multi-domain alignment for unpaired image-to-image translation
This paper addresses the problem of inferring unseen cross-domain and cr...
research
∙
12/01/2018
Cross-Modulation Networks for Few-Shot Learning
A family of recent successful approaches to few-shot learning relies on ...
research
∙
09/17/2018
Learning Effective RGB-D Representations for Scene Recognition
Deep convolutional networks (CNN) can achieve impressive results on RGB ...
research
∙
09/06/2018
Memory Replay GANs: learning to generate images from new categories without forgetting
Previous works on sequential learning address the problem of forgetting ...
research
∙
09/01/2018
LIUM-CVC Submissions for WMT18 Multimodal Translation Task
This paper describes the multimodal Neural Machine Translation systems d...
research
∙
05/04/2018
Transferring GANs: generating images from limited data
Transferring the knowledge of pretrained networks to new domains by mean...
research
∙
04/06/2018
Mix and match networks: encoder-decoder alignment for zero-pair image translation
We address the problem of image translation between domains or modalitie...
research
∙
02/08/2018
Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting
In this paper we propose an approach to avoiding catastrophic forgetting...
research
∙
01/22/2018
Food recognition and recipe analysis: integrating visual content, context and external knowledge
The central role of food in our individual and social life, combined wit...
research
∙
01/21/2018
Scene recognition with CNNs: objects, scales and dataset bias
Since scenes are composed in part of objects, accurate recognition of sc...
research
∙
01/21/2018
Depth CNNs for RGB-D scene recognition: learning from scratch better than transferring from RGB-CNNs
Scene recognition with RGB images has been extensively studied and has r...
research
∙
09/04/2017
Domain-adaptive deep network compression
Deep Neural Networks trained on large datasets can be easily transferred...
research
∙
07/14/2017