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- Licheng JiaoSuggested from co-authorship
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Works148 from public data
- 1,548
- 1,147
- Multiobjective Immune Algorithm with Nondominated Neighbor-Based Selection486
The statistical analysis based on three performance metrics show that the unique selection method is effective, and NNIA is an effective algorithm for solving multiobjective optimization problems.
- 484
- Unsupervised Feature Learning for RGB-D Based Object Recognition394
HMP uses sparse coding to learn hierarchical feature representations from raw RGB-D data in an unsupervised way and enables superior object recognition results using linear support vector machines.
- 392
- Kernel Descriptors for Visual Recognition375
This work highlights the kernel view of orientation histograms, and shows that they are equivalent to a certain type of match kernels over image patches, and designs a family of kernel descriptors which provide a unified and principled framework to turn pixel attributes into compact patch-level features.
- 348
- A Joint Model of Language and Perception for Grounded Attribute Learning324
This work presents an approach for joint learning of language and perception models for grounded attribute induction, which includes a language model based on a probabilistic categorial grammar that enables the construction of compositional meaning representations.
- Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression314
A novel loss function is proposed, named Adaptive Wing loss, that is able to adapt its shape to different types of ground truth heatmap pixels, that penalizes loss more on foreground pixels while less on background pixels.
- Discriminatively Trained Sparse Code Gradients for Contour Detection291
This work shows that contour detection accuracy can be significantly improved by computing Sparse Code Gradients (SCG), which measure contrast using patch representations automatically learned through sparse coding, which is verified on the NYU Depth Dataset.
- Twin Gaussian Processes for Structured Prediction279
Twin Gaussian processes (TGP), a generic structured prediction method that uses Gaussian process priors on both covariates and responses, both multivariate, and estimates outputs by minimizing the Kullback-Leibler divergence between two GP modeled as normal distributions over finite index sets of training and testing examples, is described.
- 277
- Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation271
A Knowledge-Enhanced Hierarchical Graph Transformer Network (KHGT) is proposed, to investigate multi-typed interactive patterns between users and items in recommender systems and consistently outperforms many state-of-the-art recommendation methods across various evaluation settings.
- Efficient Match Kernel between Sets of Features for Visual Recognition265
It is shown that bag-of-words representations commonly used in conjunction with linear classifiers can be viewed as special match kernels, which count 1 if two local features fall into the same regions partitioned by visual words and 0 otherwise.
- 263
- Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network251
A new traffic prediction framework–Spatial-Temporal Graph Diffusion Network (ST-GDN) is developed which learns not only the local region-wise geographical dependencies, but also the spatial semantics from a global perspective, and a multi-scale attention network is developed to empower ST-G DN with the capability of capturing multi-level temporal dynamics.
- Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms238
This paper proposes hierarchical matching pursuit (HMP), which builds a feature hierarchy layer-by-layer using an efficient matching pursuit encoder that includes three modules: batch (tree) orthogonal matching pursuit, spatial pyramid max pooling, and contrast normalization.
- Knowledge-aware Coupled Graph Neural Network for Social Recommendation233
A Knowledge-aware Coupled Graph Neural Network (KCGN) that jointly injects the inter-dependent knowledge across items and users into the recommendation framework and enables the high-order user- and item-wise relation encoding by exploiting the mutual information for global graph structure awareness.
- 231
- RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D217
This paper proposes to learn a generalizable Normal-Depth diffusion model for 3D generation by training on the large-scale LAION dataset together with the generalizable image-to-depth and normal prior models, and introduces an albedo diffusion model to impose data-driven constraints on the albedo component.
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- StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal196
StableNormal represents a baby attempt to repurpose diffusion priors for deterministic estimation of surface normal estimation, and evidence that StableNormal retains both the "stability" and "sharpness" for accurate normal estimation is evidence.
- 188
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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