38 citations · 62 across the 6 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…