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09/05/2023
Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples
Referring video object segmentation (RVOS), as a supervised learning tas...
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09/02/2023
Knowledge Graph Embeddings for Multi-Lingual Structured Representations of Radiology Reports
The way we analyse clinical texts has undergone major changes over the l...
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08/22/2023
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models
Pre-trained vision-language models, e.g., CLIP, working with manually de...
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07/08/2023
Learning Variational Neighbor Labels for Test-Time Domain Generalization
This paper strives for domain generalization, where models are trained e...
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06/08/2023
EMO: Episodic Memory Optimization for Few-Shot Meta-Learning
Few-shot meta-learning presents a challenge for gradient descent optimiz...
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05/17/2023
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
Meta-learning algorithms are able to learn a new task using previously l...
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05/17/2023
CageViT: Convolutional Activation Guided Efficient Vision Transformer
Recently, Transformers have emerged as the go-to architecture for both v...
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03/31/2023
SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail
Modern image classifiers perform well on populated classes, while degrad...
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03/29/2023
Implicit Diffusion Models for Continuous Super-Resolution
Image super-resolution (SR) has attracted increasing attention due to it...
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03/20/2023
Parameter-Free Channel Attention for Image Classification and Super-Resolution
The channel attention mechanism is a useful technique widely employed in...
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02/28/2023
Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning
Multimodal few-shot learning is challenging due to the large domain gap ...
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02/22/2023
Energy-Based Test Sample Adaptation for Domain Generalization
In this paper, we propose energy-based sample adaptation at test time fo...
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02/17/2023
CK-Transformer: Commonsense Knowledge Enhanced Transformers for Referring Expression Comprehension
The task of multimodal referring expression comprehension (REC), aiming ...
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10/19/2022
Variational Model Perturbation for Source-Free Domain Adaptation
We aim for source-free domain adaptation, where the task is to deploy a ...
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10/13/2022
Probabilistic Integration of Object Level Annotations in Chest X-ray Classification
Medical image datasets and their annotations are not growing as fast as ...
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10/10/2022
Association Graph Learning for Multi-Task Classification with Category Shifts
In this paper, we focus on multi-task classification, where related clas...
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04/12/2022
LifeLonger: A Benchmark for Continual Disease Classification
Deep learning models have shown a great effectiveness in recognition of ...
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03/05/2022
Fusion-Correction Network for Single-Exposure Correction and Multi-Exposure Fusion
The photographs captured by digital cameras usually suffer from over-exp...
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02/16/2022
Learning to Generalize across Domains on Single Test Samples
We strive to learn a model from a set of source domains that generalizes...
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12/26/2021
Generative Kernel Continual learning
Kernel continual learning by <cit.> has recently emerged as a strong con...
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12/15/2021
Hierarchical Variational Memory for Few-shot Learning Across Domains
Neural memory enables fast adaptation to new tasks with just a few train...
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11/10/2021
Multi-Task Neural Processes
Neural processes have recently emerged as a class of powerful neural lat...
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11/09/2021
Variational Multi-Task Learning with Gumbel-Softmax Priors
Multi-task learning aims to explore task relatedness to improve individu...
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08/30/2021
Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation
Annotation burden has become one of the biggest barriers to semantic seg...
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07/15/2021
Variational Topic Inference for Chest X-Ray Report Generation
Automating report generation for medical imaging promises to reduce work...
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07/12/2021
Kernel Continual Learning
This paper introduces kernel continual learning, a simple but effective ...
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06/05/2021
Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation
A critical challenge faced by supervised word sense disambiguation (WSD)...
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05/14/2021
Attentional Prototype Inference for Few-Shot Semantic Segmentation
This paper aims to address few-shot semantic segmentation. While existin...
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05/09/2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Domain generalization is challenging due to the domain shift and the unc...
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05/08/2021
MetaKernel: Learning Variational Random Features with Limited Labels
Few-shot learning deals with the fundamental and challenging problem of ...
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03/19/2021
Variational Knowledge Distillation for Disease Classification in Chest X-Rays
Disease classification relying solely on imaging data attracts great int...
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12/23/2020
Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression
The Cobb angle that quantitatively evaluates the spinal curvature plays ...
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10/20/2020
Learning to Learn Variational Semantic Memory
In this paper, we introduce variational semantic memory into meta-learni...
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07/15/2020
Learning to Learn with Variational Information Bottleneck for Domain Generalization
Domain generalization models learn to generalize to previously unseen do...
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06/11/2020
Learning to Learn Kernels with Variational Random Features
In this work, we introduce kernels with random Fourier features in the m...
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07/11/2019
Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
In this work, we present an end-to-end framework to settle data associat...
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03/03/2019
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network
Crowd counting has recently attracted increasing interest in computer vi...
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01/29/2019
Two-Stream Multi-Task Network for Fashion Recognition
In this paper, we present a two-stream multi-task network for fashion re...
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12/16/2018
Model-free Tracking with Deep Appearance and Motion Features Integration
Being able to track an anonymous object, a model-free tracker is compreh...
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08/18/2018
In Defense of Single-column Networks for Crowd Counting
Crowd counting usually addressed by density estimation becomes an increa...
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04/01/2018
