activity
20162024
most citedFaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition

38 citations · 40 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training

Fenghe Tang, Ronghao Xu, Qingsong Yao +5

The generative self-supervised learning strategy exhibits remarkable learning representational capabilities. However, there is limited attention to end-to-end pre-training methods…

cs.CV2024

CARZero: Cross-Attention Alignment for Radiology Zero-Shot Classification

Haoran Lai, Qingsong Yao, Zihang Jiang +4

The advancement of Zero-Shot Learning in the medical domain has been driven forward by using pre-trained models on large-scale image-text pairs, focusing on image-text alignment. H…

cs.CV20241 cited

PostoMETRO: Pose Token Enhanced Mesh Transformer for Robust 3D Human Mesh Recovery

Wendi Yang, Zihang Jiang, Shang Zhao +1

With the recent advancements in single-image-based human mesh recovery, there is a growing interest in enhancing its performance in certain extreme scenarios, such as occlusion, wh…

eess.IV2024

DuDoUniNeXt: Dual-domain unified hybrid model for single and multi-contrast undersampled MRI reconstruction

Ziqi Gao, Yue Zhang, Xinwen Liu +2

Multi-contrast (MC) Magnetic Resonance Imaging (MRI) reconstruction aims to incorporate a reference image of auxiliary modality to guide the reconstruction process of the target mo…

cs.DC2024

Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning

Zezhong Ding, Yongan Xiang, Shangyou Wang +2

In the realm of distributed systems tasked with managing and processing large-scale graph-structured data, optimizing graph partitioning stands as a pivotal challenge. The primary…

cs.CV20231 cited

Unsupervised augmentation optimization for few-shot medical image segmentation

Quan Quan, Shang Zhao, Qingsong Yao +2

The augmentation parameters matter to few-shot semantic segmentation since they directly affect the training outcome by feeding the networks with varying perturbated samples. Howev…