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Works183 from public data
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- Transfer of Preformed Three‐Dimensional Photonic Crystals onto Dye‐Sensitized Solar Cells151
This technique allows the incorporation of photonic crystals onto independently processed devices, in which the transferred films have high optical quality.
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- Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline126
This work constructs a large-scale dataset named "RGB-D-D", in which the high-frequency component adaptively decomposed from RGB image to guide the depth map SR, and provides a fast depth map super-resolution (FDSR) baseline.
- A parallel down-up fusion network for salient object detection in optical remote sensing images108
A novel Parallel Down-up Fusion network (PDF-Net) for SOD in optical RSIs, which takes full advantage of the in-path low- and high-level features and cross-path multi-resolution features to distinguish diversely scaled salient objects and suppress the cluttered backgrounds.
- Body Joint Guided 3-D Deep Convolutional Descriptors for Action Recognition78
This paper proposes not to directly use the activations of fully connected layers of a 3-D CNN as the video feature, but to use selective convolutional layer activations to form a discriminative descriptor for video.
- Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot Learning74
A debiasing loss is proposed to pursue response consistency between seen and unseen predictions, and a semantic-motivated instance decoder strengthens accurate cross-domain interactions between the matched pair for semantic-related instance adaption, en-couraging the generation of unambiguous visual representations.
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- Progressively Complementary Network for Fisheye Image Rectification Using Appearance Flow65
This paper embeds a correction layer in skipconnection and leverage the appearance flows in different layers to pre-correct the image features and proposes a parallel complementary structure that effectively reduces the burden of the decoder by separating content reconstruction and structure correction.
- Image classification by non-negative sparse coding, correlation constrained low-rank and sparse decomposition65
An image classification framework by leveraging the non-negative sparse coding, correlation constrained low rank and sparse matrix decomposition technique (CCLR-Sc+SPM), which achieves or outperforms the state-of-the-art results on several benchmarks.
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- Causality-based CTR prediction using graph neural networks47
A causality-based CTR prediction model in the GNNs framework (Causal-GNN) integrating representations of feature graph, user graph and ad graph in the context of online advertising is developed.
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- Image classification using spatial pyramid robust sparse coding47
A new image classification method by spatial pyramid robust sparse coding (SP-RSC), which tries to find the maximum likelihood estimation solution by alternatively optimizing over the codebook and local feature coding parameters, hence is more robust to outliers than traditional sparse coding based methods.
- CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation46
A new algorithm: compatible momentum contrast with Topology Preservation, dubbed CTP is proposed, which absorbs the knowledge of the current and previous-task models to flexibly update the modal feature and transfers the knowledge of embedding across tasks while preserving the flexibility of feature adjustment.
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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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