74 citations · 237 across the 10 of their papers we have counts for
10 papers
Exploring the Physical World Adversarial Robustness of Vehicle Detection
Wei Jiang, Tianyuan Zhang, Shuangcheng Liu +3
Adversarial attacks can compromise the robustness of real-world detection models. However, evaluating these models under real-world conditions poses challenges due to resource-inte…
RobustMQ: Benchmarking Robustness of Quantized Models
Yisong Xiao, Aishan Liu, Tianyuan Zhang +3
Quantization has emerged as an essential technique for deploying deep neural networks (DNNs) on devices with limited resources. However, quantized models exhibit vulnerabilities wh…
Benchmarking the Physical-world Adversarial Robustness of Vehicle Detection
Tianyuan Zhang, Yisong Xiao, Xiaoya Zhang +2
Adversarial attacks in the physical world can harm the robustness of detection models. Evaluating the robustness of detection models in the physical world can be challenging due to…
Benchmarking the Robustness of Quantized Models
Yisong Xiao, Tianyuan Zhang, Shunchang Liu +1
Quantization has emerged as an essential technique for deploying deep neural networks (DNNs) on devices with limited resources. However, quantized models exhibit vulnerabilities wh…
MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries
Tianyuan Zhang, Xuanyao Chen, Yue Wang +2
Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-based autonomous driving system. It involves modeling 3D dynamic objects in complex scenes…
FUTR3D: A Unified Sensor Fusion Framework for 3D Detection
Xuanyao Chen, Tianyuan Zhang, Yue Wang +2
Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics. Existing multi-modal 3D detection models usually involve customized designs…
Embracing Single Stride 3D Object Detector with Sparse Transformer
Lue Fan, Ziqi Pang, Tianyuan Zhang +5
In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to input scene size is significantly smaller compared to 2D detection cases. Overlooking thi…
DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries
Yue Wang, Vitor Guizilini, Tianyuan Zhang +3
We introduce a framework for multi-camera 3D object detection. In contrast to existing works, which estimate 3D bounding boxes directly from monocular images or use depth predictio…
Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang, Zhanxing Zhu
We attempt to interpret how adversarially trained convolutional neural networks (AT-CNNs) recognize objects. We design systematic approaches to interpret AT-CNNs in both qualitativ…
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang, Tianyuan Zhang, Yiping Lu +2
Deep learning achieves state-of-the-art results in many tasks in computer vision and natural language processing. However, recent works have shown that deep networks can be vulnera…