Papers Video Frame Interpolation
“Video Frame Interpolation” 태그가 달린 논문 229편 · 필터 해제
Following Motion for Sequential Modeling in Video Frame Interpolation
State Space Models (SSMs) have surfaced as a promising architecture in Video Frame Interpolation (VFI), as they can capture long-range dependencies with linear computational complexity. However, their predefined scanning…
Video Frame InterpolationSNM-VFI: Symmetric Nonlinear Motion-Guided Generative Video Frame Interpolation
We propose Symmetric Nonlinear Motion-guided Generative Video Frame Interpolation (SNM-VFI), a training-free framework for motion-controllable generative video frame interpolation with pre-trained optical flow and video …
Video Frame InterpolationMASS: Motion-Aligned Selective Scan for Refinement in Flow-Based Video Frame Interpolation
Video frame interpolation (VFI) remains a challenging task, particularly when dealing with large, non-linear motions and complex occlusions. While flow-based methods are prevalent, they often struggle with ambiguous corr…
Video Frame InterpolationUniRED: Unified RGB-D Video Frame Interpolation with Event Guidance
High frame-rate RGB-D videos are crucial for a variety of downstream tasks, including motion analysis, dynamic scene understanding, and 3D reconstruction. However, due to hardware and sensing constraints, practical RGB-D…
Video Frame InterpolationScene Understanding3D ReconstructionDeep Slice Interpolation for Reducing Through-Plane Anisotropy and Noise in Head CT
Head computed tomography (CT) typically uses sub-millimeter in-plane resolution but 2-5 mm through-plane spacing, creating substantial anisotropy that degrades multiplanar reconstructions, volumetric measurements such as…
Video Frame InterpolationDiffST: Spatiotemporal-Aware Diffusion for Real-World Space-Time Video Super-Resolution
Diffusion-based models have shown strong performance in video super-resolution (VSR) and video frame interpolation (VFI). However, their role in the coupled space-time video super-resolution (STVSR) setting remains limit…
Space-time Video Super-resolutionVideo Frame InterpolationCan Video Diffusion Models Predict Past Frames? Bidirectional Cycle Consistency for Reversible Interpolation
Video frame interpolation aims to synthesize realistic intermediate frames between given endpoints while adhering to specific motion semantics. While recent generative models have improved visual fidelity, they predomina…
Video Frame InterpolationSelf-Supervised LearningANVIL: Accelerator-Native Video Interpolation via Codec Motion Vector Priors
Real-time 30-to-60 fps video frame interpolation on mobile neural processing units (NPUs) requires each synthesized frame within 33.3 ms. We show that mainstream flow-based video frame interpolation faces three structura…
Video Frame InterpolationEdit2Interp: Adapting Image Foundation Models from Spatial Editing to Video Frame Interpolation with Few-Shot Learning
Pre-trained image editing models exhibit strong spatial reasoning and object-aware transformation capabilities acquired from billions of image-text pairs, yet they possess no explicit temporal modeling. This paper demons…
Video Frame InterpolationImage ManipulationSpatial ReasoningFew-Shot LearningInterp3R: Continuous-time 3D Geometry Estimation with Frames and Events
In recent years, 3D visual foundation models pioneered by pointmap-based approaches such as DUSt3R have attracted a lot of interest, achieving impressive accuracy and strong generalization across diverse scenes. However,…
Video Frame InterpolationFC-VFI: Faithful and Consistent Video Frame Interpolation for High-FPS Slow Motion Video Generation
Large pre-trained video diffusion models excel in video frame interpolation but struggle to generate high fidelity frames due to reliance on intrinsic generative priors, limiting detail preservation from start and end fr…
Video Frame InterpolationVideo GenerationUniE2F: A Unified Diffusion Framework for Event-to-Frame Reconstruction with Video Foundation Models
Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity changes rather than absolute intensity, the resulting data streams suff…
Video Frame InterpolationTowards Holistic Modeling for Video Frame Interpolation with Auto-regressive Diffusion Transformers
Existing video frame interpolation (VFI) methods often adopt a frame-centric approach, processing videos as independent short segments (e.g., triplets), which leads to temporal inconsistencies and motion artifacts. To ov…
Video Frame InterpolationSG-RIFE: Semantic-Guided Real-Time Intermediate Flow Estimation with Diffusion-Competitive Perceptual Quality
Real-time Video Frame Interpolation (VFI) has long been dominated by flow-based methods like RIFE, which offer high throughput but often fail in complicated scenarios involving large motion and occlusion. Conversely, rec…
parameter-efficient fine-tuningVideo Frame InterpolationDESSERT: Diffusion-based Event-driven Single-frame Synthesis via Residual Training
Video frame prediction extrapolates future frames from previous frames, but suffers from prediction errors in dynamic scenes due to the lack of information about the next frame. Event cameras address this limitation by c…
Video Frame InterpolationEvent-based Optical FlowBeyond Boundary Frames: Context-Centric Video Interpolation with Audio-Visual Semantics
Video frame interpolation has long been challenged by limited controllability and interactivity, especially in scenarios involving fast, highly non-linear, and fine-grained motion. Although recent interactive interpolati…
Video Frame InterpolationHybrid Event Frame Sensors: Modeling, Calibration, and Simulation
Hybrid event-frame sensors integrate an Event Vision Sensor (EVS) and an Active Pixel Sensor (APS) within a single chip, combining the high dynamic range and low latency of the EVS with the rich spatial intensity informa…
Video Frame InterpolationVTinker: Guided Flow Upsampling and Texture Mapping for High-Resolution Video Frame Interpolation
Due to large pixel movement and high computational cost, estimating the motion of high-resolution frames is challenging. Thus, most flow-based Video Frame Interpolation (VFI) methods first predict bidirectional flows at …
Video Frame InterpolationMiVID: Multi-Strategic Self-Supervision for Video Frame Interpolation using Diffusion Model
Video Frame Interpolation (VFI) remains a cornerstone in video enhancement, enabling temporal upscaling for tasks like slow-motion rendering, frame rate conversion, and video restoration. While classical methods rely on …
Video Frame InterpolationVideo RestorationVideo EnhancementLearning Event-guided Exposure-agnostic Video Frame Interpolation via Adaptive Feature Blending
Exposure-agnostic video frame interpolation (VFI) is a challenging task that aims to recover sharp, high-frame-rate videos from blurry, low-frame-rate inputs captured under unknown and dynamic exposure conditions. Event …
Video Frame Interpolation