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Works114 from public data
- 260
- Regional Semantic Contrast and Aggregation for Weakly Supervised Semantic Segmentation206
This work proposes regional semantic contrast and aggregation (RCA), equipped with a regional memory bank to store massive, diverse object patterns appearing in training data, which acts as strong support for exploration of dataset-level semantic structure.
- Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification186
A Noise Resistible Mutual-Training (NRMT) method, which maintains two networks during training to perform collaborative clustering and mutual instance selection, which outperforms the state-of-the-art UDA methods for person re-ID.
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- Robust LSTM-Autoencoders for Face De-Occlusion in the Wild175
A robust LSTM-Autoencoders (RLA) model is proposed to effectively restore partially occluded faces even in the wild and provides significantly larger performance gain than other de-occlusion methods in promoting recognition performance over partially-occluded faces.
- Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis169
Experimental results show that the proposed Dual-Agent Generative Adversarial Network (DA-GAN) model not only presents compelling perceptual results but also significantly outperforms state-of-the-arts on the large-scale and challenging NIST IJB-A unconstrained face recognition benchmark.
- Look across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition104
This work proposes a deep Age-Invariant Model (AIM) for face recognition in the wild with three distinct novelties, and proposes a new large-scale Cross-Age Face Recognition (CAFR) benchmark dataset to facilitate existing efforts and push the frontiers of age-invariant face recognition research.
- Beyond Monocular Deraining: Parallel Stereo Deraining Network Via Semantic Prior78
A Paired Rain Removal Network (PRRNet), which exploits both stereo images and semantic information is presented, and a Semantic-Aware Deraining Module (SADM) is developed which solves both tasks of semantic segmentation and deraining of scenes.
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- Dynamic Conditional Networks for Few-Shot Learning70
This paper proposes a novel Dynamic Conditional Convolutional Network (DCCN) to handle conditional few-shot learning, i.e, only a few training samples are available for each condition, and evaluates DCCN on four tasks which can be formulated as conditional model learning.
- Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry68
This work proposes a novel Residual RETargeting network (R2ET) structure, which relies on two neural modification modules, to adjust the source motions to fit the target skeletons and shapes progressively, and presents a balancing gate to conduct linear interpolation between them.
- Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstruction65
AnchorUDF represents 3D shapes by predicting unsigned distance fields (UDFs) to enable open garment surface modeling at arbitrary resolution and achieves the state-of-the-art performance on single-view garment reconstruction.
- Attentive WaveBlock: Complementarity-Enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-Identification and Beyond64
A novel light-weight module, the Attentive WaveBlock (AWB), which can be integrated into the dual networks of mutual learning to enhance the complementarity and further depress noise in the pseudo-labels is proposed.
- Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification.62
A novel light-weight module, the Attentive WaveBlock (AWB), which can be integrated into the dual networks of mutual learning to enhance the complementarity and further depress noise in the pseudo-labels is proposed.
- Beyond Monocular Deraining: Stereo Image Deraining via Semantic Understanding55
A Paired Rain Removal Network (PRRNet) is presented, which exploits both stereo images and semantic information, and a Semantic-Aware Deraining Module (SADM) which solves both tasks of semantic segmentation and deraining of scenes, and a Semantic-Fusion Network (SFNet) and a View-Fusion Network (VFNet) which fuse semantic information and multi-view information respectively.
- Multi-Prototype Networks for Unconstrained Set-based Face Recognition52
A novel Multi-Prototype Network (MPNet) model is proposed to learn multiple prototype face representations adaptively from the media sets to demonstrate superiority of the proposed model over state-of-the-arts.
- Robust Face Recognition with Deep Multi-View Representation Learning47
This paper describes the proposed method targeting at the MSR Image Recognition Challenge MS-Celeb-1M, to recognize one million celebrities from their face images captured in the real world, which provides a large scale dataset crawled from the Web, which contains a large number of celebrities with many images for each subject.
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- A Combined Model Based on Feature Selection and WOA for PM2.5 Concentration Forecasting30
The proposed hybrid model based on feature selection and whale optimization algorithm for the prediction of P M 2.5 concentration is better than benchmark models, such as single LSSVM model with default parameters optimization, single BP neural networks (BPNN), general regression neural network (GRNN) and some other combined models recently reported.
- Deep Attribute-preserving Metric Learning for Natural Language Object Retrieval28
A deep Attribute-Preserving Metric learning (AP-Metric) framework that jointly generates unique query-sensitive region proposals and conducts novel cross-modal feature learning that explicitly pursues consistency over semantic attribute abstraction within both domains for deep metric learning is proposed.
- Sparsity Adaptive Matching Pursuit Detection Algorithm Based on Compressed Sensing for Radar Signals26
The application of the emerging compressed sensing (CS) theory and the geometric characteristics of the targets in radar images are investigated and a novel sparsity adaptive matching pursuit (SAMP) detection algorithm is proposed, which adaptively completes the detection task without knowing the signal sparsity.
- Integrated Face Analytics Networks through Cross-Dataset Hybrid Training26
An integrated Face Analytics Network (iFAN) is proposed, which is able to perform multiple tasks jointly for face analytics with a novel carefully designed network architecture to fully facilitate the informative interaction among different tasks.
- On initial Brain Activity Mapping of episodic and semantic memory code in the hippocampus26
It is shown that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics, and it is concluded that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination.
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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