4 code implementations • 9 Mar 2024 • Xiao Wang, Ju Huang, Shiao Wang, Chuanming Tang, Bo Jiang, Yonghong Tian, Jin Tang, Bin Luo
Current event-/frame-event based trackers undergo evaluation on short-term tracking datasets, however, the tracking of real-world scenarios involves long-term tracking, and the performance of existing tracking algorithms in these scenarios remains unclear.
no code implementations • 30 Oct 2023 • Chuanming Tang, Kai Wang, Joost Van de Weijer, Jianlin Zhang, YongMei Huang
Moreover, the effectiveness of discriminative trackers remains constrained due to the adoption of the dual-branch pipeline.
1 code implementation • 30 Oct 2023 • Chuanming Tang, Kai Wang, Joost Van de Weijer
Based on this observation, we develop an iterative inversion (IterInv) technique for this category of T2I models and verify IterInv with the open-source DeepFloyd-IF model. Specifically, IterInv employ NTI as the inversion and reconstruction of low-resolution image generation.
4 code implementations • 26 Sep 2023 • Xiao Wang, Shiao Wang, Chuanming Tang, Lin Zhu, Bo Jiang, Yonghong Tian, Jin Tang
Tracking using bio-inspired event cameras has drawn more and more attention in recent years.
2 code implementations • 20 Nov 2022 • Chuanming Tang, Xiao Wang, Ju Huang, Bo Jiang, Lin Zhu, Jianlin Zhang, YaoWei Wang, Yonghong Tian
In this paper, we propose a single-stage backbone network for Color-Event Unified Tracking (CEUTrack), which achieves the above functions simultaneously.
Ranked #3 on Object Tracking on COESOT
1 code implementation • 18 Aug 2022 • Chuanming Tang, Xiao Wang, Yuanchao Bai, Zhe Wu, Jianlin Zhang, YongMei Huang
To handle these issues, in this paper, we propose a unified Spatial-Frequency Transformer that models the Gaussian spatial Prior and High-frequency emphasis Attention (GPHA) simultaneously.
no code implementations • 22 Jul 2021 • Siyuan Yi, Xing Chen, Chuanming Tang
Based on the Transformer, we proposed a time series Transformer (Tsformer) with Encoder-Decoder architecture for tourism demand forecasting.