Video Frame Interpolation
94 papers with code • 20 benchmarks • 12 datasets
The goal of Video Frame Interpolation is to synthesize several frames in the middle of two adjacent frames of the original video. Video Frame Interpolation can be applied to generate slow motion video, increase video frame rate, and frame recovery in video streaming.
Benchmarks
These leaderboards are used to track progress in Video Frame Interpolation
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Libraries
Use these libraries to find Video Frame Interpolation models and implementationsDatasets
UCF101
DAVIS
GoPro
Middlebury
Vimeo90K
X4K1000FPS
MSU Video Frame Interpolation
Inter4K
SlowFlow
ATD-12K
Subtasks
Latest papers with no code
Video Frame Interpolation with Many-to-many Splatting and Spatial Selective Refinement
In this work, we first propose a fully differentiable Many-to-Many (M2M) splatting framework to interpolate frames efficiently.
Three-Stage Cascade Framework for Blurry Video Frame Interpolation
Besides, experiments on real-world blurry videos also indicate the good generalization ability of our model.
SportsSloMo: A New Benchmark and Baselines for Human-centric Video Frame Interpolation
We re-train several state-of-the-art methods on our benchmark, and the results show a decrease in their accuracy compared to other datasets.
Uncertainty-Guided Spatial Pruning Architecture for Efficient Frame Interpolation
We can use dynamic spatial pruning method to skip redundant computation, but this method cannot properly identify easy regions in VFI tasks without supervision.
Video Frame Interpolation with Flow Transformer
Specifically, we design a Flow Transformer Block that calculates the temporal self-attention in a matched local area with the guidance of flow, making our framework suitable for interpolating frames with large motion while maintaining reasonably low complexity.
Revisiting Event-based Video Frame Interpolation
We therefore propose to incorporate RGB information in an event-guided optical flow refinement strategy.
Video Frame Interpolation with Stereo Event and Intensity Camera
The stereo event-intensity camera setup is widely applied to leverage the advantages of both event cameras with low latency and intensity cameras that capture accurate brightness and texture information.
Efficient Convolution and Transformer-Based Network for Video Frame Interpolation
This network reduces the memory burden by close to 50% and runs up to four times faster during inference time compared to existing transformer-based interpolation methods.
Self-supervised Learning of Event-guided Video Frame Interpolation for Rolling Shutter Frames
Although events possess high temporal resolution, beneficial for video frame interpolation (VFI), a hurdle in tackling this task is the lack of paired GS frames.
SPDER: Semiperiodic Damping-Enabled Object Representation
We present a neural network architecture designed to naturally learn a positional embedding and overcome the spectral bias towards lower frequencies faced by conventional implicit neural representation networks.
