218 citations · 432 across the 6 of their papers we have counts for
6 papers
SViTT: Temporal Learning of Sparse Video-Text Transformers
Yi Li, Kyle Min, Subarna Tripathi +1
Do video-text transformers learn to model temporal relationships across frames? Despite their immense capacity and the abundance of multimodal training data, recent work has reveal…
Global and Local Contrastive Self-Supervised Learning for Semantic Segmentation of HR Remote Sensing Images
Haifeng Li, Yi Li, Guo Zhang +4
Supervised learning for semantic segmentation requires a large number of labeled samples, which is difficult to obtain in the field of remote sensing. Self-supervised learning (SSL…
Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation
Xinyu Wang, Hanxi Li, Yi Li +2
Visual tracking is a fundamental problem in computer vision. Recently, some deep-learning-based tracking algorithms have been achieving record-breaking performances. However, due t…
In a World That Counts: Clustering and Detecting Fake Social Engagement at Scale
Yixuan Li, Oscar Martinez, Xing Chen +2
How can web services that depend on user generated content discern fake social engagement activities by spammers from legitimate ones? In this paper, we focus on the social site of…
Learning Discriminative Representations for Semantic Cross Media Retrieval
Aiwen Jiang, Hanxi Li, Yi Li +1
Heterogeneous gap among different modalities emerges as one of the critical issues in modern AI problems. Unlike traditional uni-modal cases, where raw features are extracted and d…
DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
Hanxi Li, Yi Li, Fatih Porikli
Deep neural networks, albeit their great success on feature learning in various computer vision tasks, are usually considered as impractical for online visual tracking because they…