Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning
Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy computational burden of state-of-the-art models hinders their deployment on resource-constrained edge devices. In this work, we identify the prediction head as a critical but often overlooked efficiency bottleneck. By strategically streamlining the decoder architecture, we unlock the potential for real-time inference but simultaneously introduce a capacity gap between the lightweight student and the heavy teacher. To resolve this, we conduct a systematic analysis of 17 distillation strategies and introduce a Dual-Alignment Distillation fr...
| Authors | Yuqi Li, Yuedong Tan, Huiran Duan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 2 August 2026 |
| Last updated at source | 2 August 2026 |
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