Autoregressive Visual Tracking
Xi'an Jiaotong University · Zhejiang University
Abstract
We present ARTrack, an autoregressive framework for visual object tracking. ARTrack tackles tracking as a coordinate sequence interpretation task that estimates object trajectories progressively, where the current estimate is induced by previous states and in turn affects subsequences. This time-autoregressive approach models the sequential evolution of trajectories to keep tracing the object across frames, making it superior to existing template matching based trackers that only consider the per-frame localization accuracy. ARTrack is simple and direct, eliminating customized localization heads and post-processings. Despite its simplicity, ARTrack achieves state-of-the-art performance on prevailing benchmark…
Citation impact
- FWCI
- 32.14
- Percentile
- 100%
- References
- 95
Authors
5Topics & keywords
- Autoregressive model
- Computer science
- BitTorrent tracker
- Benchmark (surveying)
- Artificial intelligence
- Frame (networking)
- Object (grammar)
- Code (set theory)