665 citations · 4.5k across the 236 of their papers we have counts for
21 papers · 1 filter
QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity
Siyu Huang, Jie An, Donglai Wei +2
The mechanism of existing style transfer algorithms is by minimizing a hybrid loss function to push the generated image toward high similarities in both content and style. However,…
Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators
Haitian Zheng, Zhe Lin, Jingwan Lu +8
Structure-guided image completion aims to inpaint a local region of an image according to an input guidance map from users. While such a task enables many practical applications fo…
PromptCap: Prompt-Guided Task-Aware Image Captioning
Yushi Hu, Hang Hua, Zhengyuan Yang +3
Knowledge-based visual question answering (VQA) involves questions that require world knowledge beyond the image to yield the correct answer. Large language models (LMs) like GPT-3…
Stare at What You See: Masked Image Modeling without Reconstruction
Hongwei Xue, Peng Gao, Hongyang Li +4
Masked Autoencoders (MAE) have been prevailing paradigms for large-scale vision representation pre-training. By reconstructing masked image patches from a small portion of visible…
Learning a Grammar Inducer from Massive Uncurated Instructional Videos
Songyang Zhang, Linfeng Song, Lifeng Jin +4
Video-aided grammar induction aims to leverage video information for finding more accurate syntactic grammars for accompanying text. While previous work focuses on building systems…
TLDW: Extreme Multimodal Summarisation of News Videos
Peggy Tang, Kun Hu, Lei Zhang +2
Multimodal summarisation with multimodal output is drawing increasing attention due to the rapid growth of multimedia data. While several methods have been proposed to summarise vi…
FeDXL: Provable Federated Learning for Deep X-Risk Optimization
Zhishuai Guo, Rong Jin, Jiebo Luo +1
In this paper, we tackle a novel federated learning (FL) problem for optimizing a family of X-risks, to which no existing FL algorithms are applicable. In particular, the objective…
CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Representation Alignment
Hongwei Xue, Yuchong Sun, Bei Liu +4
The pre-trained image-text models, like CLIP, have demonstrated the strong power of vision-language representation learned from a large scale of web-collected image-text data. In l…
Remote Medication Status Prediction for Individuals with Parkinson's Disease using Time-series Data from Smartphones
Weijian Li, Wei Zhu, E. Ray Dorsey +1
Medication for neurological diseases such as the Parkinson's disease usually happens remotely away from hospitals. Such out-of-lab environments pose challenges in collecting timely…
Bi-Calibration Networks for Weakly-Supervised Video Representation Learning
Fuchen Long, Ting Yao, Zhaofan Qiu +3
The leverage of large volumes of web videos paired with the searched queries or surrounding texts (e.g., title) offers an economic and extensible alternative to supervised video re…
Stand-Alone Inter-Frame Attention in Video Models
Fuchen Long, Zhaofan Qiu, Yingwei Pan +3
Motion, as the uniqueness of a video, has been critical to the development of video understanding models. Modern deep learning models leverage motion by either executing spatio-tem…
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization
Hang Hua, Xingjian Li, Dejing Dou +2
The advent of large-scale pre-trained language models has contributed greatly to the recent progress in natural language processing. Many state-of-the-art language models are first…
Automatic Relation-aware Graph Network Proliferation
Shaofei Cai, Liang Li, Xinzhe Han +3
Graph neural architecture search has sparked much attention as Graph Neural Networks (GNNs) have shown powerful reasoning capability in many relational tasks. However, the currentl…
Localized Adversarial Domain Generalization
Wei Zhu, Le Lu, Jing Xiao +3
Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attent…
Deep Federated Anomaly Detection for Multivariate Time Series Data
Wei Zhu, Dongjin Song, Yuncong Chen +6
Despite the fact that many anomaly detection approaches have been developed for multivariate time series data, limited effort has been made on federated settings in which multivari…
Explainable Fairness in Recommendation
Yingqiang Ge, Juntao Tan, Yan Zhu +7
Existing research on fairness-aware recommendation has mainly focused on the quantification of fairness and the development of fair recommendation models, neither of which studies…
Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Auto-Encoders
Wei Xiong, Neil Yeung, Shubo Wang +3
Objective and Impact Statement. We adopt a deep learning model for bone osteolysis prediction on computed tomography (CT) images of murine breast cancer bone metastases. Given the…
Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning
Kai Zhu, Wei Zhai, Yang Cao +2
Non-exemplar class-incremental learning is to recognize both the old and new classes when old class samples cannot be saved. It is a challenging task since representation optimizat…
CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Training
Haitian Zheng, Zhe Lin, Jingwan Lu +7
Recent image inpainting methods have made great progress but often struggle to generate plausible image structures when dealing with large holes in complex images. This is partiall…
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network
Jian Kang, Yan Zhu, Yinglong Xia +2
Graph Convolutional Network (GCN) plays pivotal roles in many real-world applications. Despite the successes of GCN deployment, GCN often exhibits performance disparity with respec…
Cross-modal Contrastive Distillation for Instructional Activity Anticipation
Zhengyuan Yang, Jingen Liu, Jing Huang +4
In this study, we aim to predict the plausible future action steps given an observation of the past and study the task of instructional activity anticipation. Unlike previous antic…