215 citations · 382 across the 20 of their papers we have counts for
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Learning from the Tangram to Solve Mini Visual Tasks
Yizhou Zhao, Liang Qiu, Pan Lu +3
Current pre-training methods in computer vision focus on natural images in the daily-life context. However, abstract diagrams such as icons and symbols are common and important in…
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
Pan Lu, Liang Qiu, Jiaqi Chen +6
Current visual question answering (VQA) tasks mainly consider answering human-annotated questions for natural images. However, aside from natural images, abstract diagrams with sem…
X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph
Yuan Liang, Weinan Song, Jiawei Yang +3
3D teeth reconstruction from X-ray is important for dental diagnosis and many clinical operations. However, no existing work has explored the reconstruction of teeth for a whole ca…
STAR: Sparse Transformer-based Action Recognition
Feng Shi, Chonghan Lee, Liang Qiu +6
The cognitive system for human action and behavior has evolved into a deep learning regime, and especially the advent of Graph Convolution Networks has transformed the field in rec…
Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation
Yuan Liang, Weinan Song, Jiawei Yang +3
Convolutional networks (ConvNets) have achieved promising accuracy for various anatomical segmentation tasks. Despite the success, these methods can be sensitive to data appearance…