Temporal Pyramid Structure for Video Frame Interpolation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The most prevalent structure in video frame interpolation involves using optical flow to guide frame warping, typically considering only the two adjacent frames. These methods often fail to capture long-range temporal dependencies and lead to great deformation in complex motion scenarios. Using analytical video processing knowledge, we propose a novel Temporal Pyramid Attention (TPA) block, which employs a temporal pyramid structure to connect four frames within a sliding window for the generation of intermediate frames. The temporal pyramid structure consists of three layers to leverage features at different levels to estimate the frame window and connect with GRU to produce a bi-directional feature flow. The dual pyramid structure incorporates channel attention mechanisms, enabling the interpolation of three frames in a single process. The TPA block leverages a multi-scale approach to effectively capture temporal dependencies and spatial correlations, enhancing the quality of interpolated frames. Our model achieves state-of-the-art performance on the Vimeo90K septuplet dataset compared to existing methods with pre-trained parameters.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it