Search Results for author: Chenyou Fan

Found 19 papers, 8 papers with code

Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth Estimation

no code implementations9 Mar 2023 Junjie Hu, Chenyou Fan, Liguang Zhou, Qing Gao, Honghai Liu, Tin Lun Lam

In this paper, we seek to enable lifelong learning for MDE, which performs cross-domain depth learning sequentially, to achieve high plasticity on a new domain and maintain good stability on original domains.

Depth Prediction Monocular Depth Estimation

Progressive Self-Distillation for Ground-to-Aerial Perception Knowledge Transfer

1 code implementation29 Aug 2022 Junjie Hu, Chenyou Fan, Mete Ozay, Hua Feng, Yuan Gao, Tin Lun Lam

In this paper, we introduce the ground-to-aerial perception knowledge transfer and propose a progressive semi-supervised learning framework that enables drone perception using only labeled data of ground viewpoint and unlabeled data of flying viewpoints.

Autonomous Driving Knowledge Distillation +1

Data-free Dense Depth Distillation

no code implementations26 Aug 2022 Junjie Hu, Chenyou Fan, Mete Ozay, Hualie Jiang, Tin Lun Lam

We study data-free knowledge distillation (KD) for monocular depth estimation (MDE), which learns a lightweight model for real-world depth perception tasks by compressing it from a trained teacher model while lacking training data in the target domain.

Image Classification Knowledge Distillation +1

Deep Depth Completion from Extremely Sparse Data: A Survey

no code implementations11 May 2022 Junjie Hu, Chenyu Bao, Mete Ozay, Chenyou Fan, Qing Gao, Honghai Liu, Tin Lun Lam

Depth completion aims at predicting dense pixel-wise depth from an extremely sparse map captured from a depth sensor, e. g., LiDARs.

3D Reconstruction Autonomous Driving +2

Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth

no code implementations8 Sep 2021 Chongyang Wang, Yuan Gao, Chenyou Fan, Junjie Hu, Tin Lun Lam, Nicholas D. Lane, Nadia Bianchi-Berthouze

For such issues, we propose a novel Learning to Agreement (Learn2Agree) framework to tackle the challenge of learning from multiple annotators without objective ground truth.

Federated Few-Shot Learning with Adversarial Learning

no code implementations1 Apr 2021 Chenyou Fan, Jianwei Huang

In this paper, we propose a federated few-shot learning (FedFSL) framework to learn a few-shot classification model that can classify unseen data classes with only a few labeled samples.

Federated Learning Few-Shot Learning

Projection Robust Wasserstein Distance and Riemannian Optimization

no code implementations NeurIPS 2020 Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael. I. Jordan

Projection robust Wasserstein (PRW) distance, or Wasserstein projection pursuit (WPP), is a robust variant of the Wasserstein distance.

Riemannian optimization

Federated Generative Adversarial Learning

no code implementations7 May 2020 Chenyou Fan, Ping Liu

This work studies training generative adversarial networks under the federated learning setting.

Federated Learning Style Transfer

Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering

1 code implementation CVPR 2019 Chenyou Fan, Xiaofan Zhang, Shu Zhang, Wensheng Wang, Chi Zhang, Heng Huang

In this paper, we propose a novel end-to-end trainable Video Question Answering (VideoQA) framework with three major components: 1) a new heterogeneous memory which can effectively learn global context information from appearance and motion features; 2) a redesigned question memory which helps understand the complex semantics of question and highlights queried subjects; and 3) a new multimodal fusion layer which performs multi-step reasoning by attending to relevant visual and textual hints with self-updated attention.

Question Answering Video Question Answering +1

Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient

1 code implementation1 Jun 2018 Tianyi Lin, Chenyou Fan, Mengdi Wang, Michael. I. Jordan

Convex composition optimization is an emerging topic that covers a wide range of applications arising from stochastic optimal control, reinforcement learning and multi-stage stochastic programming.

reinforcement-learning Reinforcement Learning (RL)

Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos

no code implementations ECCV 2018 Mingze Xu, Chenyou Fan, Yuchen Wang, Michael S. Ryoo, David J. Crandall

In this paper, we wish to solve two specific problems: (1) given two or more synchronized third-person videos of a scene, produce a pixel-level segmentation of each visible person and identify corresponding people across different views (i. e., determine who in camera A corresponds with whom in camera B), and (2) given one or more synchronized third-person videos as well as a first-person video taken by a mobile or wearable camera, segment and identify the camera wearer in the third-person videos.

Improved Oracle Complexity of Variance Reduced Methods for Nonsmooth Convex Stochastic Composition Optimization

no code implementations7 Feb 2018 Tianyi Lin, Chenyou Fan, Mengdi Wang

We consider the nonsmooth convex composition optimization problem where the objective is a composition of two finite-sum functions and analyze stochastic compositional variance reduced gradient (SCVRG) methods for them.

Multi-Task Spatiotemporal Neural Networks for Structured Surface Reconstruction

1 code implementation11 Jan 2018 Mingze Xu, Chenyou Fan, John D Paden, Geoffrey C. Fox, David J. Crandall

Deep learning methods have surpassed the performance of traditional techniques on a wide range of problems in computer vision, but nearly all of this work has studied consumer photos, where precisely correct output is often not critical.

Structured Prediction Surface Reconstruction

Forecasting Hands and Objects in Future Frames

no code implementations20 May 2017 Chenyou Fan, Jangwon Lee, Michael S. Ryoo

The key idea is that (1) an intermediate representation of a convolutional object recognition model abstracts scene information in its frame and that (2) we can predict (i. e., regress) such representations corresponding to the future frames based on that of the current frame.

object-detection Object Detection +1

Identifying First-person Camera Wearers in Third-person Videos

no code implementations CVPR 2017 Chenyou Fan, Jang-Won Lee, Mingze Xu, Krishna Kumar Singh, Yong Jae Lee, David J. Crandall, Michael S. Ryoo

We consider scenarios in which we wish to perform joint scene understanding, object tracking, activity recognition, and other tasks in environments in which multiple people are wearing body-worn cameras while a third-person static camera also captures the scene.

Activity Recognition Object Tracking +1

DeepDiary: Automatic Caption Generation for Lifelogging Image Streams

1 code implementation12 Aug 2016 Chenyou Fan, David J. Crandall

Lifelogging cameras capture everyday life from a first-person perspective, but generate so much data that it is hard for users to browse and organize their image collections effectively.

Image Captioning Image Retrieval +1

Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters

1 code implementation26 May 2016 AJ Piergiovanni, Chenyou Fan, Michael S. Ryoo

In this paper, we newly introduce the concept of temporal attention filters, and describe how they can be used for human activity recognition from videos.

Action Classification Action Recognition In Videos +1

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