To handle graphs in which features or connectivities are evolving over t...
Change detection (CD) is a fundamental and important task for monitoring...
In recent years, the use of multi-modal pre-trained Transformers has led...
Weakly supervised object localization (WSOL) is one of the most popular ...
Pulmonary nodules and masses are crucial imaging features in lung cancer...
Advanced image tampering techniques are increasingly challenging the
tru...
Relying on large-scale training data with pixel-level labels, previous e...
Buildings are the basic carrier of social production and human life; roa...
The efficacy of building footprint segmentation from remotely sensed ima...
Change detection (CD) is an important yet challenging task in the Earth
...
Federated learning (FL) has drawn increasing attention owing to its pote...
Optimizer is an essential component for the success of deep learning, wh...
A pooling operation is essential for effective graph-level representatio...
Universal Information Extraction (UIE) has been introduced as a unified
...
Accurately detecting lane lines in 3D space is crucial for autonomous
dr...
We focus on the weakly-supervised audio-visual video parsing task (AVVP)...
Color-guided depth super-resolution (DSR) is an encouraging paradigm tha...
Masked language modeling, widely used in discriminative language model (...
Token dropping is a recently-proposed strategy to speed up the pretraini...
This paper studies multiparty learning, aiming to learn a model using th...
Recent neural architecture search (NAS) based approaches have made great...
Wearing face mask is an effective measure to reduce the risk of COVID-19...
Cross domain pulmonary nodule detection suffers from performance degrada...
Hyperspectral change detection plays an essential role of monitoring the...
Robust generalization aims to tackle the most challenging data distribut...
Masked Image Modeling (MIM) is a new self-supervised vision pre-training...
Lung cancer is the leading cause of cancer death worldwide. The best sol...
Weakly-Supervised Semantic Segmentation (WSSS) using image-level labels
...
Very-high-resolution (VHR) remote sensing (RS) image change detection (C...
Recently, ChatGPT has attracted great attention, as it can generate flue...
This technical report briefly describes our JDExplore d-team's submissio...
Visible-infrared person re-identification (VI-ReID) aims to retrieve ima...
Adversarial imitation learning has become a widely used imitation learni...
Font generation is a difficult and time-consuming task, especially in th...
This technical report briefly describes our JDExplore d-team's Vega v2
s...
Deep reinforcement learning (DRL) is becoming increasingly popular in
im...
Fine-tuning large pretrained language models on a limited training corpu...
Unsupervised multimodal change detection is a practical and challenging ...
Few-shot visual recognition refers to recognize novel visual concepts fr...
Prompt-tuning, which freezes pretrained language models (PLMs) and only
...
Convolutional neural networks (CNNs) have been demonstrated to be highly...
Few-shot part segmentation aims to separate different parts of an object...
Graph Neural Networks (GNNs) tend to suffer from high computation costs ...
3D reconstruction of pulmonary segments plays an important role in surgi...
Sequence-to-sequence (seq2seq) learning has become a popular trend for
p...
Overfitting widely exists in adversarial robust training of deep network...
Graph neural networks have emerged as a leading architecture for many
gr...
Existing deep learning-based change detection methods try to elaborately...
Weakly-supervised semantic segmentation (WSSS) with image-level labels i...
Recently, Vision Transformer (ViT) has achieved promising performance in...