activity
20162023
most citedAIM: Adapting Image Models for Efficient Video Action Recognition

62 citations · 150 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2023★ 4 cited

SimCon Loss with Multiple Views for Text Supervised Semantic Segmentation

Yash Patel, Yusheng Xie, Yi Zhu +2

Learning to segment images purely by relying on the image-text alignment from web data can lead to sub-optimal performance due to noise in the data. The noise comes from the sample…

cs.CV2023★ 62 cited

AIM: Adapting Image Models for Efficient Video Action Recognition

Taojiannan Yang, Yi Zhu, Yusheng Xie +3

Recent vision transformer based video models mostly follow the ``image pre-training then finetuning" paradigm and have achieved great success on multiple video benchmarks. However,…

cs.LG2022

Towards Differential Relational Privacy and its use in Question Answering

Simone Bombari, Alessandro Achille, Zijian Wang +6

Memorization of the relation between entities in a dataset can lead to privacy issues when using a trained model for question answering. We introduce Relational Memorization (RM) t…

cs.CV2021★ 2 cited

LaTr: Layout-Aware Transformer for Scene-Text VQA

Ali Furkan Biten, Ron Litman, Yusheng Xie +2

We propose a novel multimodal architecture for Scene Text Visual Question Answering (STVQA), named Layout-Aware Transformer (LaTr). The task of STVQA requires models to reason over…

cs.CV2021★ 36 cited

TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation

Haoyu Ma, Liangjian Chen, Deying Kong +7

Estimating the 2D human poses in each view is typically the first step in calibrated multi-view 3D pose estimation. But the performance of 2D pose detectors suffers from challengin…

cs.CV2021★ 4 cited

DocFormer: End-to-End Transformer for Document Understanding

Srikar Appalaraju, Bhavan Jasani, Bhargava Urala Kota +2

We present DocFormer -- a multi-modal transformer based architecture for the task of Visual Document Understanding (VDU). VDU is a challenging problem which aims to understand docu…

cs.CV2020★ 2 cited

MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation

Liangjian Chen, Shih-Yao Lin, Yusheng Xie +2

Estimating 3D hand poses from a single RGB image is challenging because depth ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh annotations and…

cs.CV2020★ 3 cited

Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos

Liangjian Chen, Shih-Yao Lin, Yusheng Xie +2

Estimating 3D hand pose directly from RGB imagesis challenging but has gained steady progress recently bytraining deep models with annotated 3D poses. Howeverannotating 3D poses is…

cs.CV2020

DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation

Liangjian Chen, Shih-Yao Lin, Yusheng Xie +3

Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formati…

cs.CV2020★ 10 cited

Towards Good Practices in Self-supervised Representation Learning

Srikar Appalaraju, Yi Zhu, Yusheng Xie +1

Self-supervised representation learning has seen remarkable progress in the last few years. More recently, contrastive instance learning has shown impressive results compared to it…

cs.CV2020★ 7 cited

MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis

Zhenyu Wu, Duc Hoang, Shih-Yao Lin +5

Estimating the 3D hand pose from a monocular RGB image is important but challenging. A solution is training on large-scale RGB hand images with accurate 3D hand keypoint annotation…

cs.CV2018★ 16 cited

Generating Realistic Training Images Based on Tonality-Alignment Generative Adversarial Networks for Hand Pose Estimation

Liangjian Chen, Shih-Yao Lin, Yusheng Xie +5

Hand pose estimation from a monocular RGB image is an important but challenging task. The main factor affecting its performance is the lack of a sufficiently large training dataset…

cs.AI2018★ 2 cited

On the Generation of Medical Question-Answer Pairs

Sheng Shen, Yaliang Li, Nan Du +7

Question answering (QA) has achieved promising progress recently. However, answering a question in real-world scenarios like the medical domain is still challenging, due to the req…

cs.LG2016★ 2 cited

Variational hybridization and transformation for large inaccurate noisy-or networks

Yusheng Xie, Nan Du, Wei Fan +2

Variational inference provides approximations to the computationally intractable posterior distribution in Bayesian networks. A prominent medical application of noisy-or Bayesian n…