FSMC-Pose: Frequency and Spatial Fusion with Multiscale Self-calibration for Cattle Mounting Pose Estimation
Mounting posture is an important visual indicator of estrus in dairy cattle. However, achieving reliable mounting pose estimation in real-world environments remains challenging due to cluttered backgrounds and frequent inter-animal occlusion. We present FSMC-Pose, a top-down framework that integrates a lightweight frequency-spatial fusion backbone, CattleMountNet, and a multiscale self-calibration head, SC2Head. Specifically, we design two algorithmic components for CattleMountNet: the Spatial Frequency Enhancement Block (SFEBlock) and the Receptive Aggregation Block (RABlock). SFEBlock separates cattle from cluttered backgrounds, while RABlock captures multiscale contextual information. ...
| Authors | Fangjing Li, Zhihai Wang, Xinxin Ding et al. |
|---|---|
| Primary category | cs.CV |
| Published | 17 March 2026 |
| Last updated at source | 17 March 2026 |
Connected in the knowledge graph
- eelianafang/MOUNT-CattleDataset · cited by
- y1665065879/MOUNT-CattleDataset · cited by
Models and datasets referencing this paper
- eelianafang/MOUNT-CattleDataset
- y1665065879/MOUNT-CattleDataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.