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Works559 from public data
- Counterfactual VQA: A Cause-Effect Look at Language Bias565
A novel counterfactual inference framework is proposed, which enables the language bias to be captured as the direct causal effect of questions on answers and reduced by subtracting the direct language effect from the total causal effect.
- Spatio-Temporal AutoEncoder for Video Anomaly Detection563
A novel model called Spatio-Temporal AutoEncoding (ST AutoEncoder or STAE), which utilizes deep neural networks to learn video representation automatically and extracts features from both spatial and temporal dimensions by performing 3-dimensional convolutions, which enhances the motion feature learning in videos.
- A generic framework of user attention model and its application in video summarization553
A generic framework of a user attention model is presented, which estimates the attentions viewers may pay to video contents, and a set of modeling methods for visual and aural attentions are proposed.
- Correlative multi-label video annotation504
A third paradigm is proposed which simultaneously classifies concepts and models correlations between them in a single step by using a novel Correlative Multi-Label (CML) framework and is compared with the state-of-the-art approaches in the first and second paradigms on the widely used TRECVID data set.
- Tag ranking496
This paper proposes a tag ranking scheme, aiming to automatically rank the tags associated with a given image according to their relevance to the image content, and applies tag ranking into three applications: tag-based image search, tag recommendation, and group recommendation.
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- Quantization Networks432
This paper provides a simple and uniform way for weights and activations quantization by formulating it as a differentiable non-linear function that will shed new lights on the interpretation of neural network quantization.
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach318
This work proposes the adoption of a Federated Learning (FL) based approach to enable privacy-preserving collaborative Machine Learning across a federation of independent DaaS providers for the development of IoV applications, e.g., for traffic prediction and car park occupancy management.
- Feature Pyramid Transformer317
This work proposes a fully active feature interaction across both space and scales, called Feature Pyramid Transformer (FPT), which transforms any feature pyramid into another feature pyramid of the same size but with richer contexts, by using three specially designed transformers in self-level, top-down, and bottom-up interaction fashion.
- A Survey on Deep Hashing Methods278
This survey detailedly investigates current deep hashing algorithms including deep supervised hashing and deep unsupervised hashing, and categorizes deep supervised hash methods into pairwise methods, ranking-based methods, pointwise methods as well as quantization according to how measuring the similarities of the learned hash codes.
- Camera-Aware Proxies for Unsupervised Person Re-Identification268
This paper proposes to split each single cluster into multiple proxies and each proxy represents the instances coming from the same camera, and designs both intra and inter-camera contrastive learning components for the Re-ID model to effectively learn the ID discrimination ability within and across cameras.
- HoMM: Higher-Order Moment Matching for Unsupervised Domain Adaptation268
This work proposes a Higher-order Moment Matching (HoMM) method, and further extends the HoMM into reproducing kernel Hilbert spaces (RKHS) and shows that the first-order HoMM is equivalent to Maximum Mean Discrepancy (MMD) and the second-orders are equivalent to Correlation Alignment (CORAL).
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- Active learning in multimedia annotation and retrieval255
A survey on the efforts of leveraging active learning in multimedia annotation and retrieval, including semi-supervised learning, multilabel learning and multiple instance learning, focuses on two application domains: image/video annotation and content-based image retrieval.
- Counterfactual Zero-Shot and Open-Set Visual Recognition249
A novel counterfactual framework for both Zero-Shot Learning (ZSL) and Open-Set Recognition (OSR), whose common challenge is generalizing to the unseen-classes by only training on the seen-classes is presented.
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- Class Re-Activation Maps for Weakly-Supervised Semantic Segmentation235
An embarrassingly simple yet surprisingly effective method: Reactivating the converged CAM with BCE by using softmax crossentropy loss (SCE), dubbed ReCAM, which not only generates high-quality masks, but also supports plug-and-play in any CAM variant with little overhead.
- Gradient Centralization: A New Optimization Technique for Deep Neural Networks228
It is shown that GC can regularize both the weight space and output feature space so that it can boost the generalization performance of DNNs, and improves the Lipschitzness of the loss function and its gradient so that the training process becomes more efficient and stable.
- Distilling Causal Effect of Data in Class-Incremental Learning218
The proposed causal effect distillation method can improve various state-of-the-art CIL methods by a large margin and capture the Incremental Momentum Effect of the data stream, which can help to retain the old effect overwhelmed by the new data effect, and thus alleviate the forgetting of the old class in testing.
- PLBP: An effective local binary patterns texture descriptor with pyramid representation212
The conventional local binary pattern is extended to pyramid transform domain (PLBP) by cascading the LBP information of hierarchical spatial pyramids, PLBP descriptors take texture resolution variations into account and show their effectiveness for texture representation.
- Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization200
This paper introduces Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, and introduces this framework as GI-ReID, which enables an efficient and latency-free person identity matching for surveillance.
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- Flickr distance183
Both subjective user study and objective evaluation show that Flickr distance is more coherent to human perception than Google distance, which makes it a more reasonable distance metric.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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