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20182023
most citedVisual Tuning

36 citations · 48 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023★ 1 cited

GLA-GCN: Global-local Adaptive Graph Convolutional Network for 3D Human Pose Estimation from Monocular Video

Bruce X. B. Yu, Zhi Zhang, Yongxu Liu +3

3D human pose estimation has been researched for decades with promising fruits. 3D human pose lifting is one of the promising research directions toward the task where both estimat…

cs.CV2023★ 36 cited

Visual Tuning

Bruce X. B. Yu, Jianlong Chang, Haixin Wang +9

Fine-tuning visual models has been widely shown promising performance on many downstream visual tasks. With the surprising development of pre-trained visual foundation models, visu…

cs.CV2020★ 5 cited

Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos

Lifang Wu, Zhou Yang, Qi Wang +4

Many semantic events in team sport activities e.g. basketball often involve both group activities and the outcome (score or not). Motion patterns can be an effective means to ident…

cs.CV2019★ 1 cited

Ontology Based Global and Collective Motion Patterns for Event Classification in Basketball Videos

Lifang Wu, Zhou Yang, Jiaoyu He +4

In multi-person videos, especially team sport videos, a semantic event is usually represented as a confrontation between two teams of players, which can be represented as collectiv…

cs.CV2019★ 5 cited

AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations

Guo-Jun Qi, Liheng Zhang, Chang Wen Chen +1

The learning of Transformation-Equivariant Representations (TERs), which is introduced by Hinton et al. \cite{hinton2011transforming}, has been considered as a principle to reveal…

cs.CV2018

DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials)

Shuang Ma, Jianlong Fu, Chang Wen Chen +1

Unsupervised image translation, which aims in translating two independent sets of images, is challenging in discovering the correct correspondences without paired data. Existing wo…