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README.md
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@@ -22,7 +22,7 @@ Traditional highlight detection assumes a single, event-centric notion of salien
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- **Event** — event-driven semantic peaks, adopting the replay-based annotations from Mr. HiSum.
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- **Emotion** — affective facial moments, annotated via a scalable two-stage automatic pipeline (frame-level facial expression recognition + multimodal LLM verification).
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- **Nature** — aesthetic scenic highlights, annotated via scenic localization (person/landscape detection) followed by frame-level aesthetic scoring.
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The three perspectives are intentionally complementary rather than redundant (cross-perspective IoU as low as 0.002–0.052 on Mr. HiSum), enabling structured analysis of heterogeneous highlight patterns beyond the traditional single-perspective paradigm. This repository provides only the precomputed CLIP ViT-B/32 features (and Emotion ground-truth labels) used in the paper's experiments — see the paper for full annotation pipeline details.
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| Emotion | 5-second averaged windows | 512 | float16 | binary highlight labels + segment metadata (separate archive) |
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| Event | 1 FPS | 512 | float32 | frame-level replay-saliency scores (separate archive) |
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| Nature |
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All features are stored per-clip as individual `.npz` files, packaged into numbered zip shards for download.
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### Nature
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- `nature/nature_feat_part_{1..32}.zip` — per-video feature files, each `.npz` with key `features` of shape `(T, 512)`. Files suffixed `_aug` are augmented variants of their base video.
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- `nature/nature_gt_part_1.zip` — matching ground-truth files, each `.json` containing a list of per-
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- `nature/nature_split.json` — `train_keys` / `val_keys` / `test_keys` (12,763 / 874 / 1,903 clips).
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Feature and ground-truth files share the same base filename (e.g. `--rd0X_LQCo.npz` / `--rd0X_LQCo.json`) across the two archive sets.
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- **Event** — event-driven semantic peaks, adopting the replay-based annotations from Mr. HiSum.
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- **Emotion** — affective facial moments, annotated via a scalable two-stage automatic pipeline (frame-level facial expression recognition + multimodal LLM verification).
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- **Nature** — aesthetic scenic highlights, annotated via scenic localization (person/landscape detection) followed by frame-level aesthetic scoring. Features are sampled at 1 FPS, same as Event.
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The three perspectives are intentionally complementary rather than redundant (cross-perspective IoU as low as 0.002–0.052 on Mr. HiSum), enabling structured analysis of heterogeneous highlight patterns beyond the traditional single-perspective paradigm. This repository provides only the precomputed CLIP ViT-B/32 features (and Emotion ground-truth labels) used in the paper's experiments — see the paper for full annotation pipeline details.
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|---------|-----------------------------|-------------|---------|--------------|
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| Emotion | 5-second averaged windows | 512 | float16 | binary highlight labels + segment metadata (separate archive) |
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| Event | 1 FPS | 512 | float32 | frame-level replay-saliency scores (separate archive) |
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| Nature | 1 FPS | 512 | float16 | frame-level aesthetic scores (separate archive); includes `_aug` augmented variants |
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All features are stored per-clip as individual `.npz` files, packaged into numbered zip shards for download.
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### Nature
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- `nature/nature_feat_part_{1..32}.zip` — per-video feature files, each `.npz` with key `features` of shape `(T, 512)`, sampled at 1 FPS. Files suffixed `_aug` are augmented variants of their base video.
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- `nature/nature_gt_part_1.zip` — matching ground-truth files, each `.json` containing a list of per-frame aesthetic saliency scores in `[0, 1]`, aligned with the feature sequence.
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- `nature/nature_split.json` — `train_keys` / `val_keys` / `test_keys` (12,763 / 874 / 1,903 clips).
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Feature and ground-truth files share the same base filename (e.g. `--rd0X_LQCo.npz` / `--rd0X_LQCo.json`) across the two archive sets.
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