Bernt Schiele, Fisher Yu, Mattia Segu
We lifted 3 functions out of this paper's own repositories and ran 3 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| mattiasegu/darth | canonical | 3 of 3 |
| Function | Status | Where it lives |
|---|---|---|
| majority_vote | Ran | mattiasegu/darth/darth/core/track/postprocessing.py code served (permissive licence) · get_code("d322dd3188b65f75") |
| random_color | Ran | mattiasegu/darth/darth/core/utils/visualization.py code served (permissive licence) · get_code("f5582ad06308b3d9") |
| xyxy2xywh | Ran | mattiasegu/darth/darth/core/to_scalabel/utils.py code served (permissive licence) · get_code("443a802f0281709c") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Multiple object tracking (MOT) is a fundamental component of perception systems for autonomous driving, and its robustness to unseen conditions is a requirement to avoid life-critical failures. Despite the urge of safety in driving systems, no solution to the MOT adaptation problem to domain shift in test-time conditions has ever been proposed. However, the nature of a MOT system is manifold -requiring object detection and instance association -and adapting all its components is non-trivial. In this paper, we analyze the effect of domain shift on appearance-based trackers, and introduce DARTH, a holistic test-time adaptation framework for MOT. We propose a detection consistency formulation to adapt object detection in a self-supervised fashion, while adapting the instance appearance representations via our novel patch contrastive loss. We evaluate our method on a variety of domain shifts -including sim-toreal, outdoor-to-indoor, indoor-to-outdoor -and substantially improve the source model performance on all metrics.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2310.01926")
get_code_for_paper("2310.01926")
have("2310.01926")
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