355 citations · 471 across the 17 of their papers we have counts for
17 papers
AIMS: All-Inclusive Multi-Level Segmentation
Lu Qi, Jason Kuen, Weidong Guo +5
Despite the progress of image segmentation for accurate visual entity segmentation, completing the diverse requirements of image editing applications for different-level region-of-…
High-Quality Entity Segmentation
Lu Qi, Jason Kuen, Weidong Guo +5
Dense image segmentation tasks e.g., semantic, panoptic) are useful for image editing, but existing methods can hardly generalize well in an in-the-wild setting where there are unr…
MAT: Mask-Aware Transformer for Large Hole Image Inpainting
Wenbo Li, Zhe Lin, Kun Zhou +3
Recent studies have shown the importance of modeling long-range interactions in the inpainting problem. To achieve this goal, existing approaches exploit either standalone attentio…
High Quality Segmentation for Ultra High-resolution Images
Tiancheng Shen, Yuechen Zhang, Lu Qi +5
To segment 4K or 6K ultra high-resolution images needs extra computation consideration in image segmentation. Common strategies, such as down-sampling, patch cropping, and cascade…
CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation
Lu Qi, Jason Kuen, Zhe Lin +7
To improve instance-level detection/segmentation performance, existing self-supervised and semi-supervised methods extract either task-unrelated or task-specific training signals f…
Image Synthesis via Semantic Composition
Yi Wang, Lu Qi, Ying-Cong Chen +2
In this paper, we present a novel approach to synthesize realistic images based on their semantic layouts. It hypothesizes that for objects with similar appearance, they share simi…
Multi-Scale Aligned Distillation for Low-Resolution Detection
Lu Qi, Jason Kuen, Jiuxiang Gu +5
In instance-level detection tasks (e.g., object detection), reducing input resolution is an easy option to improve runtime efficiency. However, this option traditionally hurts the…
ICM-3D: Instantiated Category Modeling for 3D Instance Segmentation
Ruihang Chu, Yukang Chen, Tao Kong +2
Separating 3D point clouds into individual instances is an important task for 3D vision. It is challenging due to the unknown and varying number of instances in a scene. Existing d…
Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision
Yanwei Li, Hengshuang Zhao, Xiaojuan Qi +6
In this paper, we present a conceptually simple, strong, and efficient framework for fully- and weakly-supervised panoptic segmentation, called Panoptic FCN. Our approach aims to r…
Open-World Entity Segmentation
Lu Qi, Jason Kuen, Yi Wang +5
We introduce a new image segmentation task, called Entity Segmentation (ES), which aims to segment all visual entities (objects and stuffs) in an image without predicting their sem…
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond
Wenbo Li, Kun Zhou, Lu Qi +3
Single image super-resolution (SISR) deals with a fundamental problem of upsampling a low-resolution (LR) image to its high-resolution (HR) version. Last few years have witnessed i…
Scale-aware Automatic Augmentation for Object Detection
Yukang Chen, Yanwei Li, Tao Kong +4
We propose Scale-aware AutoAug to learn data augmentation policies for object detection. We define a new scale-aware search space, where both image- and box-level augmentations are…
Best-Buddy GANs for Highly Detailed Image Super-Resolution
Wenbo Li, Kun Zhou, Lu Qi +4
We consider the single image super-resolution (SISR) problem, where a high-resolution (HR) image is generated based on a low-resolution (LR) input. Recently, generative adversarial…
MuCAN: Multi-Correspondence Aggregation Network for Video Super-Resolution
Wenbo Li, Xin Tao, Taian Guo +3
Video super-resolution (VSR) aims to utilize multiple low-resolution frames to generate a high-resolution prediction for each frame. In this process, inter- and intra-frames are th…
PointINS: Point-based Instance Segmentation
Lu Qi, Yi Wang, Yukang Chen +4
In this paper, we explore the mask representation in instance segmentation with Point-of-Interest (PoI) features. Differentiating multiple potential instances within a single PoI f…
Sequential Context Encoding for Duplicate Removal
Lu Qi, Shu Liu, Jianping Shi +1
Duplicate removal is a critical step to accomplish a reasonable amount of predictions in prevalent proposal-based object detection frameworks. Albeit simple and effective, most pre…
Path Aggregation Network for Instance Segmentation
Shu Liu, Lu Qi, Haifang Qin +2
The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in pro…