81 citations · 186 across the 9 of their papers we have counts for
14 papers
Adaptive-Gravity: A Defense Against Adversarial Samples
Ali Mirzaeian, Zhi Tian, Sai Manoj P D +4
This paper presents a novel model training solution, denoted as Adaptive-Gravity, for enhancing the robustness of deep neural network classifiers against adversarial examples. We c…
NAS-FCOS: Efficient Search for Object Detection Architectures
Ning Wang, Yang Gao, Hao Chen +4
Neural Architecture Search (NAS) has shown great potential in effectively reducing manual effort in network design by automatically discovering optimal architectures. What is notew…
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation
Bowen Zhang, Yifan Liu, Zhi Tian +1
Semantic segmentation requires per-pixel prediction for a given image. Typically, the output resolution of a segmentation network is severely reduced due to the downsampling operat…
Twins: Revisiting the Design of Spatial Attention in Vision Transformers
Xiangxiang Chu, Zhi Tian, Yuqing Wang +5
Very recently, a variety of vision transformer architectures for dense prediction tasks have been proposed and they show that the design of spatial attention is critical to their s…
TFPose: Direct Human Pose Estimation with Transformers
Weian Mao, Yongtao Ge, Chunhua Shen +3
We propose a human pose estimation framework that solves the task in the regression-based fashion. Unlike previous regression-based methods, which often fall behind those state-of-…
BoxInst: High-Performance Instance Segmentation with Box Annotations
Zhi Tian, Chunhua Shen, Xinlong Wang +1
We present a high-performance method that can achieve mask-level instance segmentation with only bounding-box annotations for training. While this setting has been studied in the l…