π Introducing VideoCoF: Unified Video Editing with a Temporal Reasoner (Chain-of-Frames)!
Weβre excited to introduce VideoCoF, a unified framework for instruction-based video editing that enables temporal reasoning and ~4Γ video length extrapolation, trained with only 50k video pairs. π₯
π What makes VideoCoF different? π§ Chain-of-Frames reasoning , mimic human thinking process like Seeing β Reasoning β Editing to apply edits accurately over time without external masks, ensuring physically plausible results. π Strong length generalization β trained on 33-frame clips, yet supports multi-shot editing and long-video extrapolation (~4Γ). π― Unified fine-grained editing β Object Removal, Addition, Swap, and Local Style Transfer, with instance-level & part-level, spatial-aware control.
β‘ Fast inference update π H100: ~20s / video with 4-step inference, making high-quality video editing far more practical for real-world use.
π Introducing VideoCoF: Unified Video Editing with a Temporal Reasoner (Chain-of-Frames)!
Weβre excited to introduce VideoCoF, a unified framework for instruction-based video editing that enables temporal reasoning and ~4Γ video length extrapolation, trained with only 50k video pairs. π₯
π What makes VideoCoF different? π§ Chain-of-Frames reasoning , mimic human thinking process like Seeing β Reasoning β Editing to apply edits accurately over time without external masks, ensuring physically plausible results. π Strong length generalization β trained on 33-frame clips, yet supports multi-shot editing and long-video extrapolation (~4Γ). π― Unified fine-grained editing β Object Removal, Addition, Swap, and Local Style Transfer, with instance-level & part-level, spatial-aware control.
β‘ Fast inference update π H100: ~20s / video with 4-step inference, making high-quality video editing far more practical for real-world use.
π Introducing VideoCoF: Unified Video Editing with a Temporal Reasoner (Chain-of-Frames)!
Weβre excited to introduce VideoCoF, a unified framework for instruction-based video editing that enables temporal reasoning and ~4Γ video length extrapolation, trained with only 50k video pairs. π₯
π What makes VideoCoF different? π§ Chain-of-Frames reasoning , mimic human thinking process like Seeing β Reasoning β Editing to apply edits accurately over time without external masks, ensuring physically plausible results. π Strong length generalization β trained on 33-frame clips, yet supports multi-shot editing and long-video extrapolation (~4Γ). π― Unified fine-grained editing β Object Removal, Addition, Swap, and Local Style Transfer, with instance-level & part-level, spatial-aware control.
β‘ Fast inference update π H100: ~20s / video with 4-step inference, making high-quality video editing far more practical for real-world use.