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- Shuicheng YanSuggested from co-authorship
- Hanqing LuSuggested from co-authorship
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Works253 from public data
- Single Image Dehazing via Multi-scale Convolutional Neural Networks1,759
A multi-scale deep neural network for single-image dehazing by learning the mapping between hazy images and their corresponding transmission maps by combining a coarse-scale net which predicts a holistic transmission map based on the entire image, and a fine-scale network which refines results locally.
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- RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment558
A novel and end-to-end Alignment Generative Adversarial Network (AlignGAN) for the RGB-IR RE-ID task, which consists of a pixel generator, a feature generator and a joint discriminator that is able to not only alleviate the cross-modality and intra- modality variations, but also learn identity-consistent features.
- Robust Visual Tracking via Structured Multi-Task Sparse Learning427
The results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity.
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- Deep People Counting in Extremely Dense Crowds388
This paper proposes an end-to-end deep convolutional neural networks (CNN) regression model for counting people of images in extremely dense crowds that achieves superior performance than the state-of-the-arts in term of the mean and variance of absolute difference.
- PPDM: Parallel Point Detection and Matching for Real-Time Human-Object Interaction Detection337
A single-stage Human-Object Interaction (HOI) detection method that has outperformed all existing methods on HICO-DET dataset at 37 fps on a single Titan XP GPU is proposed, and is the first real-time HOI detection method.
- Deep Human Parsing with Active Template Regression308
In this work, the human parsing task, namely decomposing a human image into semantic fashion/body regions, is formulated as an active template regression (ATR) problem, where the normalized mask is expressed as the linear combination of the learned mask templates.
- Hi, magic closet, tell me what to wear!290
This paper collects a large clothing What-to-Wear dataset, and thoroughly annotates the whole dataset with 7 multi-value clothing attributes and 10 occasion categories via Amazon Mechanic Turk, to learn a generalize-well model and comprehensively evaluate it.
- BeautyGAN283
A dual input/output Generative Adversarial Network that enables the network to learn translation on instance-level through unsupervised adversarial learning, and could generate visually pleasant makeup faces and accurate transferring results.
- General Instance Distillation for Object Detection264
This work proposes a novel distillation method for detection tasks based on discriminative instances without considering the positive or negative distinguished by GT, which is called general instance distillation (GID).
- Robust Visual Tracking Via Consistent Low-Rank Sparse Learning261
A consistent low-rank sparse tracker that builds upon the particle filter framework for tracking that adaptively prunes and selects candidate particles by using linear sparse combinations of dictionary templates is proposed.
- Delving Into the Devils of Bird’s-Eye-View Perception: A Review, Evaluation and Recipe252
A full suite of practical guidebook to improve the performance of BEV perception tasks, including camera, LiDAR and fusion inputs is introduced, and the future research directions in this area are pointed out.
- Referring Image Segmentation via Cross-Modal Progressive Comprehension250
A Cross-Modal Progressive Comprehension (CMPC) module and a Text-Guided Feature Exchange (TGFE) module to effectively address the challenging task of referring image segmentation.
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- GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection222
Guided-Embedding Network (GEN) is proposed to attain a two-branch pipeline without post-matching and Visual-Linguistic Knowledge Transfer (VLKT) training strategy to enhance interaction understanding by transferring knowledge from a visual-linguistic pre-trained model CLIP is proposed.
- Linguistic Structure Guided Context Modeling for Referring Image Segmentation211
A "gather-propagate-distribute" scheme to model multimodal context by cross-modal interaction and implement this scheme as a novel Linguistic Structure guided Context Modeling (LSCM) module.
- Cross-Modal Progressive Comprehension for Referring Segmentation202
This paper proposes a cross-modal progressive comprehension (CMPC) scheme to effectively mimic human behaviors and implements it as a CMPC-I (Image) module and aCMPC-V (Video) module to improve referring image and video segmentation models.
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- Reformulating HOI Detection as Adaptive Set Prediction190
This paper reformulate HOI detection as an adaptive set prediction problem, with this novel formulation, it is proposed an Adaptive Set-based one-stage framework (AS-Net) with parallel instance and interaction branches and an effective instance-aware attention module.
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- Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding171
This paper proposes the triad-level matching and reconstruction modules which are lightweight yet effective for the weakly-supervised training, making it three times lighter and faster than the previous state-of-the-art methods.
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 2026-10-13. 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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