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Video Frame Interpolation
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
AceVFI: A Comprehensive Survey of Advances in Video Frame Interpolation
PS4PRO: Pixel-to-pixel Supervision for Photorealistic Rendering and Optimization
EventDiff: A Unified and Efficient Diffusion Model Framework for Event-based Video Frame Interpolation
TimeTracker: Event-based Continuous Point Tracking for Video Frame Interpolation with Non-linear Motion
Time-adaptive Video Frame Interpolation based on Residual Diffusion
Coupled Video Frame Interpolation and Encoding with Hybrid Event Cameras for Low-Power High-Framerate Video
Video Motion Graphs
EGVD: Event-Guided Video Diffusion Model for Physically Realistic Large-Motion Frame Interpolation
EDEN: Enhanced Diffusion for High-quality Large-motion Video Frame Interpolation
Inversion-Free Video Style Transfer with Trajectory Reset Attention Control and Content-Style Bridging
Event-Based Video Frame Interpolation With Cross-Modal Asymmetric Bidirectional Motion Fields
Semantic-Aware Adaptive Video Streaming Using Latent Diffusion Models for Wireless Networks
Generative AI Empowered Semantic Feature Multiple Access (SFMA) Over Wireless Networks
Single Trajectory Distillation for Accelerating Image and Video Style Transfer
Adapting Image-to-Video Diffusion Models for Large-Motion Frame Interpolation
GaraMoSt: Parallel Multi-Granularity Motion and Structural Modeling for Efficient Multi-Frame Interpolation in DSA Images
BiM-VFI: directional Motion Field-Guided Frame Interpolation for Video with Non-uniform Motions
StyleMaster: Stylize Your Video with Artistic Generation and Translation
Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation
SfM-Free 3D Gaussian Splatting via Hierarchical Training
UniVST: A Unified Framework for Training-free Localized Video Style Transfer
High-Resolution Frame Interpolation with Patch-based Cascaded Diffusion
Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunities
Z-upscaling: Optical Flow Guided Frame Interpolation for Isotropic Reconstruction of 3D EM Volumes
Noise Crystallization and Liquid Noise: Zero-shot Video Generation using Image Diffusion Models
SelfDRSC++: Self-Supervised Learning for Dual Reversed Rolling Shutter Correction
360VFI: A Dataset and Benchmark for Omnidirectional Video Frame Interpolation
Mono-ViFI: A Unified Learning Framework for Self-supervised Single- and Multi-frame Monocular Depth Estimation
Generalizable Implicit Motion Modeling for Video Frame Interpolation
MoSt-DSA: Modeling Motion and Structural Interactions for Direct Multi-Frame Interpolation in DSA Images
VFIMamba: Video Frame Interpolation with State Space Models
Investigating Event-Based Cameras for Video Frame Interpolation in Sports
Disentangled Motion Modeling for Video Frame Interpolation
Video Frame Interpolation for Polarization via Swin-Transformer
LAVIB: A Large-scale Video Interpolation Benchmark
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