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Works219 from public data
- VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results259
Based on the selected 29 robust detection methods, the experimental results comprehensively are discussed, which shows the effectiveness of ensemble learning and data augmentation in drone captured object detection.
- Beyond pixels: A comprehensive survey from bottom-up to semantic image segmentation and cosegmentation240
A comprehensive review of the recent progress in image segmentation, covering 190 publications, gives an overview of broad segmentation topics including not only the classic unsupervised methods, but also the recent weakly-/semi- supervised methods and the fully-super supervised methods.
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- Key-Word-Aware Network for Referring Expression Image Segmentation200
A key-word-aware network, which contains a query attention model and a key-words-aware visual context model, which outperforms state-of-the-art methods on two referring expression image segmentation databases.
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- A2RMNet: Adaptively Aspect Ratio Multi-Scale Network for Object Detection in Remote Sensing Images76
A novel end-to-end Adaptively Aspect Ratio Multi-Scale Network (A 2 RMNet) is proposed to solve the problem of easy to miss or incorrectly locate objects due to the various sizes and aspect ratios of objects.
- Subjective and Objective De-Raining Quality Assessment Towards Authentic Rain Image75
A de-raining quality assessment (DQA) database is created and a bi-directional feature embedding network (B-FEN) which integrates the features of global perception and local difference together is proposed which significantly outperforms many existing universal blind image quality assessment models.
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- Towards Continual Egocentric Activity Recognition: A Multi-Modal Egocentric Activity Dataset for Continual Learning59
A multi-modal egocentric activity dataset for continual activity learning named UESTC-MMEA-CL is proposed and the results of egocentric activity recognition of three modalities separately and jointly on a base network architecture are reported.
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- Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond49
The proposed PGMA-Net can solve bbox-level and cross-domain FSS, co-segmentation, zero-shot segmentation (ZSS) tasks, leading an any-shot segmentation framework capable of accommodating diverse weak or pixel annotations.
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- Global and local semantics-preserving based deep hashing for cross-modal retrieval49
A large margin is enforced between similar hash codes and dissimilar hash codes from an inter-modal view to learn discriminative hash codes, which can well preserve local semantic structure and the global semantic structure can be preserved into the hash codes.
- A SYMMETRIC FULLY CONVOLUTIONAL RESIDUAL NETWORK WITH DCRF FOR ACCURATE TOOTH SEGMENTATION48
A symmetric full convolutional network with residual block and Dense Conditional Random Field (DCRF), which can achieve accurate segmentation automatically for tooth images and can not only strengthen feature propagation, but also boost feature reuse.
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- No reference image quality assessment metric via multi-domain structural information and piecewise regression47
This paper develops a new local image representation which extracts the structural image information from both the spatial-frequency and spatial domains and develops an efficient piecewise regression method to capture the local distribution of the feature space.
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 2026-10-16. 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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