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20182022
most citedRetrieval-Augmented Generation for Code Summarization via Hybrid GNN

69 citations · 400 across the 32 of their papers we have counts for

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Showing 2021Show all

14 papers · 1 filter

cs.CV2021★ 2 cited

Benchmarking Shadow Removal for Facial Landmark Detection and Beyond

Lan Fu, Qing Guo, Felix Juefei-Xu +4

Facial landmark detection is a very fundamental and significant vision task with many important applications. In practice, facial landmark detection can be affected by a lot of nat…

cs.SE2021★ 4 cited

GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search

Shangqing Liu, Xiaofei Xie, Jingkai Siow +3

Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs su…

cs.GR2021

Constant-Cost Spatio-Angular Prefiltering of Glinty Appearance Using Tensor Decomposition

Hong Deng, Yang Liu, Beibei Wang +4

The detailed glinty appearance from complex surface microstructures enhances the level of realism, but is both space- and time-consuming to render, especially when viewed from far…

cs.CV2021

CarveNet: Carving Point-Block for Complex 3D Shape Completion

Qing Guo, Zhijie Wang, Felix Juefei-Xu +4

3D point cloud completion is very challenging because it heavily relies on the accurate understanding of the complex 3D shapes (e.g., high-curvature, concave/convex, and hollowed-o…

cs.CV2021

Learning to Adversarially Blur Visual Object Tracking

Qing Guo, Ziyi Cheng, Felix Juefei-Xu +4

Motion blur caused by the moving of the object or camera during the exposure can be a key challenge for visual object tracking, affecting tracking accuracy significantly. In this w…

cs.CV2021★ 2 cited

AdvFilter: Predictive Perturbation-aware Filtering against Adversarial Attack via Multi-domain Learning

Yihao Huang, Qing Guo, Felix Juefei-Xu +4

High-level representation-guided pixel denoising and adversarial training are independent solutions to enhance the robustness of CNNs against adversarial attacks by pre-processing…