33 citations · 61 across the 9 of their papers we have counts for
9 papers
PVP: Pre-trained Visual Parameter-Efficient Tuning
Zhao Song, Ke Yang, Naiyang Guan +3
Large-scale pre-trained transformers have demonstrated remarkable success in various computer vision tasks. However, it is still highly challenging to fully fine-tune these models…
Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration
Peng Qiao, Sidun Liu, Tao Sun +2
The great success of Deep Neural Networks (DNNs) has inspired the algorithmic development of DNN-based Fixed-Point (DNN-FP) for computer vision tasks. DNN-FP methods, trained by Ba…
Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction
Xuanzhao Wang, Zhengping Che, Bo Jiang +6
Video anomaly detection is commonly used in many applications such as security surveillance and is very challenging.A majority of recent video anomaly detection approaches utilize…
Towards Precise End-to-end Weakly Supervised Object Detection Network
Ke Yang, Dongsheng Li, Yong Dou
It is challenging for weakly supervised object detection network to precisely predict the positions of the objects, since there are no instance-level category annotations. Most exi…
Exploring Frame Segmentation Networks for Temporal Action Localization
Ke Yang, Xiaolong Shen, Peng Qiao +3
Temporal action localization is an important task of computer vision. Though many methods have been proposed, it still remains an open question how to predict the temporal location…
IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition
Ke Yang, Peng Qiao, Dongsheng Li +1
Effective spatiotemporal feature representation is crucial to the video-based action recognition task. Focusing on discriminate spatiotemporal feature learning, we propose Informat…