Search Results for author: Ya-Qin Zhang

Found 18 papers, 12 papers with code

Conditional Perceptual Quality Preserving Image Compression

no code implementations16 Aug 2023 Tongda Xu, Qian Zhang, Yanghao Li, Dailan He, Zhe Wang, Yuanyuan Wang, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang

We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information.

Image Compression

Query-Policy Misalignment in Preference-Based Reinforcement Learning

no code implementations27 May 2023 Xiao Hu, Jianxiong Li, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang

To unravel this mystery, we identify a long-neglected issue in the query selection schemes of existing PbRL studies: Query-Policy Misalignment.

reinforcement-learning

PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

1 code implementation25 May 2023 Jianxiong Li, Xiao Hu, Haoran Xu, Jingjing Liu, Xianyuan Zhan, Ya-Qin Zhang

Offline-to-online reinforcement learning (RL), by combining the benefits of offline pretraining and online finetuning, promises enhanced sample efficiency and policy performance.

reinforcement-learning Reinforcement Learning (RL)

DPF: Learning Dense Prediction Fields with Weak Supervision

1 code implementation CVPR 2023 Xiaoxue Chen, Yuhang Zheng, Yupeng Zheng, Qiang Zhou, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

We showcase the effectiveness of DPFs using two substantially different tasks: high-level semantic parsing and low-level intrinsic image decomposition.

Intrinsic Image Decomposition Scene Understanding +1

VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection

1 code implementation20 Mar 2023 Zhe Wang, Siqi Fan, Xiaoliang Huo, Tongda Xu, Yan Wang, Jingjing Liu, Yilun Chen, Ya-Qin Zhang

In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D) makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.

3D Object Detection Autonomous Driving +2

AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

no code implementations13 Mar 2023 Hao Wen, Yuanchun Li, Zunshuai Zhang, Shiqi Jiang, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, Yunxin Liu

Model elastification generates a high-quality search space of model architectures with the guidance of a developer-specified oracle model.

LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDAR

1 code implementation27 Feb 2023 Pengfei Li, Ruowen Zhao, Yongliang Shi, Hao Zhao, Jirui Yuan, Guyue Zhou, Ya-Qin Zhang

In this paper, we propose a novel Eikonal formulation that conditions the implicit representation on localized shape priors which function as dense boundary value constraints, and demonstrate it works on SemanticKITTI and SemanticPOSS.

Autonomous Driving Representation Learning

Mind the Gap: Offline Policy Optimization for Imperfect Rewards

1 code implementation3 Feb 2023 Jianxiong Li, Xiao Hu, Haoran Xu, Jingjing Liu, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang

RGM is formulated as a bi-level optimization problem: the upper layer optimizes a reward correction term that performs visitation distribution matching w. r. t.

Reinforcement Learning (RL)

Mutual Information Regularization for Vertical Federated Learning

no code implementations1 Jan 2023 Tianyuan Zou, Yang Liu, Ya-Qin Zhang

However, previous works show that parties without labels (passive parties) in VFL can infer the sensitive label information owned by the party with labels (active party) or execute backdoor attacks to VFL.

Federated Learning

Vertical Federated Learning

no code implementations23 Nov 2022 Yang Liu, Yan Kang, Tianyuan Zou, Yanhong Pu, Yuanqin He, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, Qiang Yang

Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with different features about the same set of users jointly train machine learning models without exposing their raw data or model parameters.

Federated Learning Privacy Preserving

TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation

1 code implementation19 Oct 2022 Pengfei Li, Beiwen Tian, Yongliang Shi, Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

As such, we study the challenging problem of task oriented detection, which aims to find objects that best afford an action indicated by verbs like sit comfortably on.

Instance Segmentation Referring Expression +2

When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning

2 code implementations23 May 2022 Jianxiong Li, Xianyuan Zhan, Haoran Xu, Xiangyu Zhu, Jingjing Liu, Ya-Qin Zhang

In offline reinforcement learning (RL), one detrimental issue to policy learning is the error accumulation of deep Q function in out-of-distribution (OOD) areas.

D4RL Offline RL +2

Semi-supervised Implicit Scene Completion from Sparse LiDAR

1 code implementation29 Nov 2021 Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Recent advances show that semi-supervised implicit representation learning can be achieved through physical constraints like Eikonal equations.

Representation Learning

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

1 code implementation CVPR 2022 Xiaoxue Chen, Tianyu Liu, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Multi-task indoor scene understanding is widely considered as an intriguing formulation, as the affinity of different tasks may lead to improved performance.

Scene Understanding Semantic Segmentation +1

PQ-Transformer: Jointly Parsing 3D Objects and Layouts from Point Clouds

1 code implementation12 Sep 2021 Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Such a scheme has two limitations: 1) Storing and running several networks for different tasks are expensive for typical robotic platforms.

object-detection Object Detection +2

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