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- Chi–Keung TangSuggested from co-authorship
- Heung‐Yeung ShumSuggested from co-authorship
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Works314 from public data
- Pyramid Scene Parsing Network15,291
This paper exploits the capability of global context information by different-region-based context aggregation through the pyramid pooling module together with the proposed pyramid scene parsing network (PSPNet) to produce good quality results on the scene parsing task.
- Path Aggregation Network for Instance Segmentation9,307
Path Aggregation Network (PANet) is proposed aiming at boosting information flow in proposal-based instance segmentation framework by enhancing the entire feature hierarchy with accurate localization signals in lower layers by bottom-up path augmentation.
- Point Transformer2,467
The Point Transformer design improves upon prior work across domains and tasks and crosses the 70% mIoU threshold for the first time on the challenging S3DIS dataset.
- 1,797
- ICNet for Real-Time Semantic Segmentation on High-Resolution Images1,627
An image cascade network (ICNet) that incorporates multi-resolution branches under proper label guidance to address the challenging task of real-time semantic segmentation is proposed and in-depth analysis of the framework is provided.
- Image smoothing via L 0 gradient minimization1,508
This work presents a new image editing method, particularly effective for sharpening major edges by increasing the steepness of transition while eliminating a manageable degree of low-amplitude structures in an optimization framework making use of L0 gradient minimization.
- 1,435
- 1,386
- Scale-Recurrent Network for Deep Image Deblurring1,338
A Scale-recurrent Network (SRN-DeblurNet) is proposed and shown to produce better quality results than state-of-the-arts, both quantitatively and qualitatively in single image deblurring.
- 3DSSD: Point-Based 3D Single Stage Object Detector1,220
This paper presents a lightweight point-based 3D single stage object detector 3DSSD to achieve decent balance of accuracy and efficiency, and outperforms all state-of-the-art voxel-based single-stage methods by a large margin.
- PSANet: Point-wise Spatial Attention Network for Scene Parsing1,191
The point-wise spatial attention network (PSANet) is proposed to relax the local neighborhood constraint and achieves top performance on various competitive scene parsing datasets, including ADE20K, PASCAL VOC 2012 and Cityscapes, demonstrating its effectiveness and generality.
- 1,159
- ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation1,154
This paper proposes to use scribbles to annotate images, and develops an algorithm to train convolutional networks for semantic segmentation supervised by scribbles, which shows excellent results on the PASCALCONTEXT dataset thanks to extra inexpensive scribble annotations.
- Two-Phase Kernel Estimation for Robust Motion Deblurring1,147
It is found that strong edges do not always profit kernel estimation, but instead under certain circumstance degrade it, which leads to a new metric to measure the usefulness of image edges in motion deblurring and a gradient selection process to mitigate their possible adverse effect.
- LISA: Reasoning Segmentation via Large Language Model1,078
This work proposes a new segmentation task - reasoning segmentation and presents LISA: large Language Instructed Segmentation Assistant, which inherits the language generation capabilities of multimodal Large Language Models (LLMs) while also possessing the ability to produce segmentation masks.
- Deep Convolutional Neural Network for Image Deconvolution999
This work develops a deep convolutional neural network to capture the characteristics of degradation, establishing the connection between traditional optimization-based schemes and a neural network architecture where a novel, separable structure is introduced as a reliable support for robust deconvolution against artifacts.
- 979
- Structure extraction from texture via relative total variation948
This work proposes new inherent variation and relative total variation measures, which capture the essential difference of these two types of visual forms, and develops an efficient optimization system to extract main structures.
- Exploring Self-Attention for Image Recognition946
This work considers two forms of self-attention, pairwise and patchwise, which generalizes standard dot-product attention and is fundamentally a set operator and strictly more powerful than convolution.
- STD: Sparse-to-Dense 3D Object Detector for Point Cloud866
This work proposes a two-stage 3D object detection framework, named sparse-to-dense 3D Object Detector (STD), and implements a parallel intersection-over-union (IoU) branch to increase awareness of localization accuracy, resulting in further improved performance.
- 840
- Prior Guided Feature Enrichment Network for Few-Shot Segmentation764
The PFENet consists of novel designs of a training-free prior mask generation method that not only retains generalization power but also improves model performance and Feature Enrichment Module (FEM) that overcomes spatial inconsistency by adaptively enriching query features with support features and prior masks.
- 749
- Distilling Knowledge via Knowledge Review717
For the first time in knowledge distillation, cross-stage connection paths are proposed and a new review mechanism is proposed that requires negligible computation overhead, and outperforms other methods on a variety of tasks.
- Image completion with structure propagation671
This paper introduces a novel approach to image completion in which the user manually specifies important missing structure information by extending a few curves or line segments from the known to the unknown regions by adopting the Belief Propagation algorithm to find the optimal patches.
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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