activity
20162024
most citedSalient Object Detection in Optical Remote Sensing Images Driven by Transformer

123 citations · 350 across the 16 of their papers we have counts for

collaborators

6 papers

cs.LG20228 cited

Attention Hijacking in Trojan Transformers

Weimin Lyu, Songzhu Zheng, Tengfei Ma +2

Trojan attacks pose a severe threat to AI systems. Recent works on Transformer models received explosive popularity and the self-attentions are now indisputable. This raises a cent…

cs.CV202216 cited

Expanding Language-Image Pretrained Models for General Video Recognition

Bolin Ni, Houwen Peng, Minghao Chen +5

Contrastive language-image pretraining has shown great success in learning visual-textual joint representation from web-scale data, demonstrating remarkable "zero-shot" generalizat…

cs.LG20224 cited

Prior Knowledge Guided Unsupervised Domain Adaptation

Tao Sun, Cheng Lu, Haibin Ling

The waive of labels in the target domain makes Unsupervised Domain Adaptation (UDA) an attractive technique in many real-world applications, though it also brings great challenges…

cs.CV2021118 cited

Multi-Content Complementation Network for Salient Object Detection in Optical Remote Sensing Images

Gongyang Li, Zhi Liu, Weisi Lin +1

In the computer vision community, great progresses have been achieved in salient object detection from natural scene images (NSI-SOD); by contrast, salient object detection in opti…

cs.CV201935 cited

PFLD: A Practical Facial Landmark Detector

Xiaojie Guo, Siyuan Li, Jinke Yu +5

Being accurate, efficient, and compact is essential to a facial landmark detector for practical use. To simultaneously consider the three concerns, this paper investigates a neat m…

cs.CV201613 cited

Multi-level Contextual RNNs with Attention Model for Scene Labeling

Heng Fan, Xue Mei, Danil Prokhorov +1

Context in image is crucial for scene labeling while existing methods only exploit local context generated from a small surrounding area of an image patch or a pixel, by contrast l…