84 citations · 89 across the 5 of their papers we have counts for
5 papers
AcroFOD: An Adaptive Method for Cross-domain Few-shot Object Detection
Yipeng Gao, Lingxiao Yang, Yunmu Huang +3
Under the domain shift, cross-domain few-shot object detection aims to adapt object detectors in the target domain with a few annotated target data. There exists two significant ch…
STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding
Zihang Lin, Chaolei Tan, Jian-Fang Hu +3
In this technical report, we introduce our solution to human-centric spatio-temporal video grounding task. We propose a concise and effective framework named STVGFormer, which mode…
Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning
Jia-Run Du, Jia-Chang Feng, Kun-Yu Lin +5
Weakly Supervised Temporal Action Localization (WSTAL) aims to localize and classify action instances in long untrimmed videos with only video-level category labels. Due to the lac…
SIOD: Single Instance Annotated Per Category Per Image for Object Detection
Hanjun Li, Xingjia Pan, Ke Yan +2
Object detection under imperfect data receives great attention recently. Weakly supervised object detection (WSOD) suffers from severe localization issues due to the lack of instan…
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
Yuqi Huo, Manli Zhang, Guangzhen Liu +32
Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction bet…