activity
20152026
most citedMitigating Adversarial Effects Through Randomization

194 citations · 413 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2026

HAD: Hallucination-Aware Diffusion Priors for 3D Reconstruction

Xi Liu, Weiwei Sun, Zhou Ren +3

Diffusion priors have recently demonstrated strong capability in enhancing the quality of sparse-view 3D reconstruction by augmenting training views at novel viewpoints, but they i…

cs.CV2021★ 5 cited

Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking

Yiding Yang, Zhou Ren, Haoxiang Li +3

Multi-person pose estimation and tracking serve as crucial steps for video understanding. Most state-of-the-art approaches rely on first estimating poses in each frame and only the…

cs.CV2019★ 34 cited

3D Hand Shape and Pose Estimation from a Single RGB Image

Liuhao Ge, Zhou Ren, Yuncheng Li +4

This work addresses a novel and challenging problem of estimating the full 3D hand shape and pose from a single RGB image. Most current methods in 3D hand analysis from monocular R…

cs.CV2019★ 7 cited

Streamlined Dense Video Captioning

Jonghwan Mun, Linjie Yang, Zhou Ren +2

Dense video captioning is an extremely challenging task since accurate and coherent description of events in a video requires holistic understanding of video contents as well as co…

cs.CV2018★ 5 cited

Deep Regionlets: Blended Representation and Deep Learning for Generic Object Detection

Hongyu Xu, Xutao Lv, Xiaoyu Wang +3

In this paper, we propose a novel object detection algorithm named "Deep Regionlets" by integrating deep neural networks and a conventional detection schema for accurate generic ob…

cs.NE2018★ 3 cited

An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints

Zhe Li, Xuehan Xiong, Zhou Ren +3

Recently, there emerged revived interests of designing automatic programs (e.g., using genetic/evolutionary algorithms) to optimize the structure of Convolutional Neural Networks (…

cs.CV2018★ 1 cited

Adversarial Attacks and Defences Competition

Alexey Kurakin, Ian Goodfellow, Samy Bengio +20

To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop…

cs.CV2018★ 78 cited

Improving Transferability of Adversarial Examples with Input Diversity

Cihang Xie, Zhishuai Zhang, Yuyin Zhou +4

Though CNNs have achieved the state-of-the-art performance on various vision tasks, they are vulnerable to adversarial examples --- crafted by adding human-imperceptible perturbati…

cs.CV2017★ 194 cited

Mitigating Adversarial Effects Through Randomization

Cihang Xie, Jianyu Wang, Zhishuai Zhang +2

Convolutional neural networks have demonstrated high accuracy on various tasks in recent years. However, they are extremely vulnerable to adversarial examples. For example, imperce…

cs.CV2017★ 62 cited

Deep Reinforcement Learning-based Image Captioning with Embedding Reward

Zhou Ren, Xiaoyu Wang, Ning Zhang +2

Image captioning is a challenging problem owing to the complexity in understanding the image content and diverse ways of describing it in natural language. Recent advances in deep…

cs.CV2015★ 24 cited

Multi-Instance Visual-Semantic Embedding

Zhou Ren, Hailin Jin, Zhe Lin +2

Visual-semantic embedding models have been recently proposed and shown to be effective for image classification and zero-shot learning, by mapping images into a continuous semantic…