Papers › Objects do not disappear: Video object detection by single-frame object location anticipation
Objects do not disappear: Video object detection by single-frame object location anticipation
Xin Liu, Fatemeh Karimi Nejadasl, Jan C. van Gemert, Olaf Booij, Silvia L. Pintea
Objects in videos are typically characterized by continuous smooth motion. We exploit continuous smooth motion in three ways. 1) Improved accuracy by using object motion as an additional source of supervision, which we obtain by anticipating object locations from a static keyframe. 2) Improved efficiency by only doing the expensive feature computations on a small subset of all frames. Because neighboring video frames are often redundant, we only compute features for a single static keyframe and predict object locations in subsequent frames. 3) Reduced annotation cost, where we only annotate the keyframe and use smooth pseudo-motion between keyframes. We demonstrate computational efficiency, annotation efficiency, and improved mean average precision compared to the state-of-the-art on four datasets: ImageNet VID, EPIC KITCHENS-55, YouTube-BoundingBoxes, and Waymo Open dataset. Our source code is available at https://github.com/L-KID/Videoobject-detection-by-location-anticipation.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Video Object Detection | EPIC-KITCHENS-55 | Ours (Faster RCNN) | mAP@.5 | 41.7 | #1 of 1 | Archive leaderboard | report |
| Video Object Detection | ImageNet VID | Ours (Def. DETR + SwinB) | MAP | 91.3 | #3 of 33 | Archive leaderboard | report |
| Video Object Detection | ImageNet VID | Ours (Def. DETR + R101) | MAP | 87.9 | #8 of 33 | Archive leaderboard | report |
| Video Object Detection | ImageNet VID | Ours (Faster RCNN + R101) | MAP | 87.2 | #10 of 33 | Archive leaderboard | report |
| Video Object Detection | Waymo Open Dataset | AP | 59.28 | #1 of 1 | Archive leaderboard | report | |
| Video Object Detection | YT-BB | mAP | 59.8 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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