31 citations · 67 across the 5 of their papers we have counts for
5 papers
Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer
Yanjing Li, Sheng Xu, Baochang Zhang +3
The large pre-trained vision transformers (ViTs) have demonstrated remarkable performance on various visual tasks, but suffer from expensive computational and memory cost problems…
IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors
Sheng Xu, Yanjing Li, Bohan Zeng +5
Knowledge distillation (KD) has been proven to be useful for training compact object detection models. However, we observe that KD is often effective when the teacher model and stu…
TerViT: An Efficient Ternary Vision Transformer
Sheng Xu, Yanjing Li, Teli Ma +4
Vision transformers (ViTs) have demonstrated great potential in various visual tasks, but suffer from expensive computational and memory cost problems when deployed on resource-con…
Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
Xiaolong Jiang, Peizhao Li, Yanjing Li +1
In this work, we present an end-to-end framework to settle data association in online Multiple-Object Tracking (MOT). Given detection responses, we formulate the frame-by-frame dat…
Two-Stream Multi-Task Network for Fashion Recognition
Peizhao Li, Yanjing Li, Xiaolong Jiang +1
In this paper, we present a two-stream multi-task network for fashion recognition. This task is challenging as fashion clothing always contain multiple attributes, which need to be…