[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"glossary-frame-interpolation::en":3,"gloss-cluster-frame-interpolation::en":20,"gloss-next-frame-interpolation::en":9},{"slug":4,"category":5,"name":6,"definition":7,"meta_desc":8,"faq":9,"schema_markup":9,"related":10},"frame-interpolation","output","Frame Interpolation","Frame interpolation is an AI video technique that generates entirely new, physically plausible in-between frames sitting between two existing consecutive frames of a source video, used to smooth perceived motion or convert footage from a lower to a higher frame rate (e.g., 24fps to 60fps) without simply duplicating or cross-fading frames, which is what older, non-AI interpolation methods did and which produced visible ghosting\u002Fblurring artifacts on fast motion. Neural frame-interpolation models (RIFE, DAIN, and the interpolation modules built directly into tools like Topaz Video AI and most modern AI video generators) estimate optical flow — a dense, pixel-by-pixel motion vector field describing precisely how content moved and where it will land between the two source frames — and use that motion estimate to synthesize a genuinely new intermediate frame with every object positioned correctly along its actual motion path at that fractional point in time, rather than simply cross-fading or blending raw pixel values between the two frames, which produces far smoother, more natural-looking motion, especially for fast-moving objects or complex occlusion (an object briefly passing behind another) — cases where naive frame-blending produces obvious, jarring double-exposure-style ghosting artifacts that immediately look wrong to a viewer. Why it matters for SaaS builders: frame interpolation is most directly relevant as an internal pipeline component of AI video-synthesis tools — many text-to-video and video-synthesis models natively generate at a lower frame rate (e.g., 8-16fps) for cost\u002Fspeed reasons, then apply frame interpolation as a cheaper post-processing pass to reach a smooth, standard delivery frame rate (24-60fps) rather than generating every frame directly with the much more expensive core diffusion model. It's also relevant to video-restoration\u002Fremastering SaaS products upconverting old low-frame-rate archival footage for modern displays, and to slow-motion effect tools that interpolate extra frames to stretch footage smoothly rather than simply slowing down existing frames (which looks choppy). A concrete worked example — an AI video-generation platform's cost-optimized rendering pipeline: (1) to keep GPU costs manageable, the core video-diffusion model generates a clip at 12fps; (2) rather than paying the much higher compute cost to generate natively at 24fps, the platform runs the raw 12fps output through a frame-interpolation model that generates a new synthesized frame between every pair of existing frames; (3) the result is a smooth 24fps final video at a fraction of the generation cost of native 24fps diffusion; (4) the interpolation step adds roughly 5-10 seconds of processing versus multiplying the core generation cost by 2x.","Frame interpolation uses AI to generate new in-between video frames, smoothing motion or converting footage to a higher frame rate.",null,[11,14,17],{"slug":12,"name":13},"text-to-video","Text-to-Video",{"slug":15,"name":16},"upscaling","Upscaling",{"slug":18,"name":19},"video-synthesis","Video Synthesis",[21,25,29,33,36,40,43,46,49,52,55,58],{"slug":22,"category":5,"name":23,"updated_at":24},"abstention","Abstention","2026-08-24T03:30:02+00:00",{"slug":26,"category":5,"name":27,"updated_at":28},"ai-copywriting","AI Copywriting","2026-08-24T02:46:38+00:00",{"slug":30,"category":5,"name":31,"updated_at":32},"ai-watermarking","AI Watermarking","2026-08-24T02:46:37+00:00",{"slug":34,"category":5,"name":35,"updated_at":32},"aspect-ratio-control","Aspect-Ratio Control",{"slug":37,"category":5,"name":38,"updated_at":39},"audio-generation","Audio Generation","2026-08-24T02:46:36+00:00",{"slug":41,"category":5,"name":42,"updated_at":32},"audio-super-resolution","Audio Super-Resolution",{"slug":44,"category":5,"name":45,"updated_at":39},"avatar-generation","Avatar Generation",{"slug":47,"category":5,"name":48,"updated_at":39},"background-removal","Background Removal",{"slug":50,"category":5,"name":51,"updated_at":32},"batch-image-generation","Batch Image Generation",{"slug":53,"category":5,"name":54,"updated_at":28},"brand-voice","Brand Voice",{"slug":56,"category":5,"name":57,"updated_at":28},"cfg-scale","CFG Scale (Classifier-Free Guidance)",{"slug":59,"category":5,"name":60,"updated_at":32},"character-consistency","Character Consistency"]