activity
20192024
most citedA Multi-Level Approach to Waste Object Segmentation

76 citations · 104 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness

Kejia Zhang, Juanjuan Weng, Yuanzheng Cai +2

Ensuring the robustness of deep neural networks against adversarial attacks remains a fundamental challenge in computer vision. While adversarial training (AT) has emerged as a pro…

cs.CV20241 cited

A Multi-Stage Goal-Driven Network for Pedestrian Trajectory Prediction

Xiuen Wu, Tao Wang, Yuanzheng Cai +2

Pedestrian trajectory prediction plays a pivotal role in ensuring the safety and efficiency of various applications, including autonomous vehicles and traffic management systems. T…

cs.CV202115 cited

Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification

Fengxiang Yang, Zhun Zhong, Zhiming Luo +4

This paper considers the problem of unsupervised person re-identification (re-ID), which aims to learn discriminative models with unlabeled data. One popular method is to obtain ps…

cs.CV202076 cited

A Multi-Level Approach to Waste Object Segmentation

Tao Wang, Yuanzheng Cai, Lingyu Liang +1

We address the problem of localizing waste objects from a color image and an optional depth image, which is a key perception component for robotic interaction with such objects. Sp…

cs.CV201912 cited

Learning a Layout Transfer Network for Context Aware Object Detection

Tao Wang, Xuming He, Yuanzheng Cai +1

We present a context aware object detection method based on a retrieve-and-transform scene layout model. Given an input image, our approach first retrieves a coarse scene layout fr…