Search Results for author: Jiayun Wang

Found 17 papers, 9 papers with code

Trajectory Regularization Enhances Self-Supervised Geometric Representation

no code implementations22 Mar 2024 Jiayun Wang, Stella X. Yu, Yubei Chen

To address this gap, we introduce a new pose-estimation benchmark for assessing SSL geometric representations, which demands training without semantic or pose labels and achieving proficiency in both semantic and geometric downstream tasks.

Pose Estimation Representation Learning +1

Deep Multimodal Fusion for Surgical Feedback Classification

no code implementations6 Dec 2023 Rafal Kocielnik, Elyssa Y. Wong, Timothy N. Chu, Lydia Lin, De-An Huang, Jiayun Wang, Anima Anandkumar, Andrew J. Hung

This work offers an important first look at the feasibility of automated classification of real-world live surgical feedback based on text, audio, and video modalities.


Tracking the Dynamics of the Tear Film Lipid Layer

no code implementations7 Dec 2022 Tejasvi Kothapalli, Charlie Shou, Jennifer Ding, Jiayun Wang, Andrew D. Graham, Tatyana Svitova, Stella X. Yu, Meng C. Lin

Tear film instability is a known factor for DED, and is thought to be regulated in large part by the thin lipid layer that covers and stabilizes the tear film.

Unsupervised Scene Sketch to Photo Synthesis

1 code implementation6 Sep 2022 Jiayun Wang, Sangryul Jeon, Stella X. Yu, Xi Zhang, Himanshu Arora, Yu Lou

Taking this advantage, we synthesize a photo-realistic image by combining the structure of a sketch and the visual style of a reference photo.

Open Long-Tailed Recognition in a Dynamic World

no code implementations17 Aug 2022 Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, Stella X. Yu

A practical recognition system must balance between majority (head) and minority (tail) classes, generalize across the distribution, and acknowledge novelty upon the instances of unseen classes (open classes).

Active Learning Classification +4

Compact and Optimal Deep Learning with Recurrent Parameter Generators

1 code implementation15 Jul 2021 Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann Lecun

We propose a drastically different approach to compact and optimal deep learning: We decouple the Degrees of freedom (DoF) and the actual number of parameters of a model, optimize a small DoF with predefined random linear constraints for a large model of arbitrary architecture, in one-stage end-to-end learning.

Ranked #97 on Image Classification on ObjectNet (using extra training data)

Image Classification Model Compression

Language-Guided Global Image Editing via Cross-Modal Cyclic Mechanism

no code implementations ICCV 2021 Wentao Jiang, Ning Xu, Jiayun Wang, Chen Gao, Jing Shi, Zhe Lin, Si Liu

Given the cycle, we propose several free augmentation strategies to help our model understand various editing requests given the imbalanced dataset.

3D Shape Reconstruction from Free-Hand Sketches

1 code implementation17 Jun 2020 Jiayun Wang, Jierui Lin, Qian Yu, Runtao Liu, Yubei Chen, Stella X. Yu

Additionally, we propose a sketch standardization module to handle different sketch distortions and styles.

3D Reconstruction 3D Shape Reconstruction

A Deep Learning Approach for Meibomian Gland Atrophy Evaluation in Meibography Images

1 code implementation Translational Vision Science & Technology 2019 Jiayun Wang, Thao N. Yeh, Rudrasis Chakraborty, Stella X. Yu, Meng C. Lin

The development set was used to train and tune the deep learning model, while the evaluation set was used to evaluate the performance of the model.

Orthogonal Convolutional Neural Networks

1 code implementation CVPR 2020 Jiayun Wang, Yubei Chen, Rudrasis Chakraborty, Stella X. Yu

We develop an efficient approach to impose filter orthogonality on a convolutional layer based on the doubly block-Toeplitz matrix representation of the convolutional kernel instead of using the common kernel orthogonality approach, which we show is only necessary but not sufficient for ensuring orthogonal convolutions.

Image Classification Image Retrieval

Learning Coupled Spatial-temporal Attention for Skeleton-based Action Recognition

no code implementations23 Sep 2019 Jiayun Wang

In this paper, we propose a coupled spatial-temporal attention (CSTA) model for skeleton-based action recognition, which aims to figure out the most discriminative joints and frames in spatial and temporal domains simultaneously.

Action Recognition Skeleton Based Action Recognition

Spatial Transformer for 3D Point Clouds

1 code implementation26 Jun 2019 Jiayun Wang, Rudrasis Chakraborty, Stella X. Yu

We propose a novel end-to-end approach to learn different non-rigid transformations of the input point cloud so that optimal local neighborhoods can be adopted at each layer.

Semantic Segmentation

SurReal: Fréchet Mean and Distance Transform for Complex-Valued Deep Learning

1 code implementation24 Jun 2019 Rudrasis Chakraborty, Jiayun Wang, Stella X. Yu

On RadioML, our model achieves comparable RF modulation classification accuracy at 10% of the baseline model size.

General Classification

Large-Scale Long-Tailed Recognition in an Open World

2 code implementations CVPR 2019 Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, Stella X. Yu

We define Open Long-Tailed Recognition (OLTR) as learning from such naturally distributed data and optimizing the classification accuracy over a balanced test set which include head, tail, and open classes.

Classification Few-Shot Learning +4

Successive Embedding and Classification Loss for Aerial Image Classification

1 code implementation5 Dec 2017 Jiayun Wang, Patrick Virtue, Stella X. Yu

To address the overfitting problem in aerial image classification, we consider the neural network as successive transformations of an input image into embedded feature representations and ultimately into a semantic class label, and train neural networks to optimize image representations in the embedded space in addition to optimizing the final classification score.

Classification Clustering +2

Deep Ranking Model by Large Adaptive Margin Learning for Person Re-identification

no code implementations3 Jul 2017 Jiayun Wang, Sanping Zhou, Jinjun Wang, Qiqi Hou

In this paper, we present a novel deep ranking model with feature learning and fusion by learning a large adaptive margin between the intra-class distance and inter-class distance to solve the person re-identification problem.

Person Re-Identification

Point to Set Similarity Based Deep Feature Learning for Person Re-Identification

no code implementations CVPR 2017 Sanping Zhou, Jinjun Wang, Jiayun Wang, Yihong Gong, Nanning Zheng

One of the key issues for deep learning based person Re-ID is the selection of proper similarity comparison criteria, and the performance of learned features using existing criterion based on pairwise similarity is still limited, because only P2P distances are mostly considered.

Person Re-Identification

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