Search Results for author: Cheng Chi

Found 13 papers, 5 papers with code

Exploiting Implicit Rigidity Constraints via Weight-Sharing Aggregation for Scene Flow Estimation from Point Clouds

no code implementations4 Mar 2023 Yun Wang, Cheng Chi, Xin Yang

Scene flow estimation, which predicts the 3D motion of scene points from point clouds, is a core task in autonomous driving and many other 3D vision applications.

Autonomous Driving Pose Estimation +2

Don't overfit the history -- Recursive time series data augmentation

no code implementations6 Jul 2022 Amine Mohamed Aboussalah, Min-Jae Kwon, Raj G Patel, Cheng Chi, Chi-Guhn Lee

We apply RIM to diverse real world time series cases to achieve strong performance over non-augmented data on regression, classification, and reinforcement learning tasks.

Data Augmentation Time Series Analysis

A Deep Reinforcement Learning Framework For Column Generation

no code implementations3 Jun 2022 Cheng Chi, Amine Mohamed Aboussalah, Elias B. Khalil, Juyoung Wang, Zoha Sherkat-Masoumi

Column Generation (CG) is an iterative algorithm for solving linear programs (LPs) with an extremely large number of variables (columns).

Decision Making reinforcement-learning +1

Feature-Level Collaboration: Joint Unsupervised Learning of Optical Flow, Stereo Depth and Camera Motion

no code implementations CVPR 2021 Cheng Chi, Qingjie Wang, Tianyu Hao, Peng Guo, Xin Yang

In this paper, we show that effective feature-level collaboration of the networks for the three respective tasks could achieve much greater performance improvement for all three tasks than only loss-level joint optimization.

Depth And Camera Motion Motion Estimation +4

GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion

no code implementations ICCV 2021 Cheng Chi, Shuran Song

By mapping the observed partial surface to the canonical space and completing it in this space, the output representation describes the garment's full configuration using a complete 3D mesh with the per-vertex canonical coordinate label.

3D Shape Representation Pose Estimation

Loss Function Search for Face Recognition

1 code implementation ICML 2020 Xiaobo Wang, Shuo Wang, Cheng Chi, Shifeng Zhang, Tao Mei

In face recognition, designing margin-based (e. g., angular, additive, additive angular margins) softmax loss functions plays an important role in learning discriminative features.

AutoML Face Recognition

Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

10 code implementations CVPR 2020 Shifeng Zhang, Cheng Chi, Yongqiang Yao, Zhen Lei, Stan Z. Li

In this paper, we first point out that the essential difference between anchor-based and anchor-free detection is actually how to define positive and negative training samples, which leads to the performance gap between them.

object-detection Object Detection

Relational Learning for Joint Head and Human Detection

1 code implementation24 Sep 2019 Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z. Li, Xudong Zou

Head and human detection have been rapidly improved with the development of deep convolutional neural networks.

Head Detection Human Detection +1

PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes

no code implementations15 Sep 2019 Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z. Li, Xudong Zou

Pedestrian detection in crowded scenes is a challenging problem, because occlusion happens frequently among different pedestrians.

Data Augmentation Occlusion Handling +2

RefineFace: Refinement Neural Network for High Performance Face Detection

no code implementations10 Sep 2019 Shifeng Zhang, Cheng Chi, Zhen Lei, Stan Z. Li

To improve the classification ability for high recall efficiency, STC first filters out most simple negatives from low level detection layers to reduce search space for subsequent classifier, then SML is applied to better distinguish faces from background at various scales and FSM is introduced to let the backbone learn more discriminative features for classification.

Classification Face Detection +3

Selective Refinement Network for High Performance Face Detection

3 code implementations7 Sep 2018 Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei, Stan Z. Li, Xudong Zou

In particular, the SRN consists of two modules: the Selective Two-step Classification (STC) module and the Selective Two-step Regression (STR) module.

Face Detection General Classification +2

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