3 accepted papers
We present ARTrack-AC, a new step in the autoregressive tracking paradigm that introduces adaptive capacity inference to achieve both temporal consistency and dynamic efficiency. While existing autoregressive trackers predict object states sequentially with fixed inference capacity, they fail to acc
Recent advances in diffusion models have significantly improved text-to-video generation, enabling personalized content creation with fine-grained control over both foreground and background elements. However, precise face–attribute alignment across subjects remains challenging, as existing methods…
Forecasting the future trajectories of multiple agents is a core technology for human-robot interaction systems. To predict multi-agent trajectories more accurately, it is inevitable that models need to improve interpretability and reduce redundancy. However, many methods adopt implicit weight calcu…