10 papers
Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation
Hmrishav Bandyopadhyay, Xuanchi Ren, Zijian Huang +7
Interactive autoregressive video generation demands both low-latency rollouts and precise online control. Few-step distillation accelerates generation by reducing denoising steps,…
CaricHarmony: Contrastive Diffusion Paths for Identity-Preserving Caricature Synthesis
Dongyu Wang, Dar-Yen Chen, Yi-Zhe Song
Sketch-based caricature synthesis suffers from a fundamental failure mode: when identity and shape conditions are combined in diffusion models, they create destructive interference…
Block Cascading: Training Free Acceleration of Block-Causal Video Models
Hmrishav Bandyopadhyay, Nikhil Pinnaparaju, Rahim Entezari +3
Block-causal video generation faces a stark speed-quality trade-off: small 1.3B models manage only 16 FPS while large 14B models crawl at 4.5 FPS, forcing users to choose between r…
CuriGS: Curriculum-Guided Gaussian Splatting for Sparse View Synthesis
Zijian Wu, Mingfeng Jiang, Zidian Lin +5
3D Gaussian Splatting (3DGS) has recently emerged as an efficient, high-fidelity representation for real-time scene reconstruction and rendering. However, extending 3DGS to sparse-…
SD3.5-Flash: Distribution-Guided Distillation of Generative Flows
Hmrishav Bandyopadhyay, Rahim Entezari, Jim Scott +3
We present SD3.5-Flash, an efficient few-step distillation framework that brings high-quality image generation to accessible consumer devices. Our approach distills computationally…
MotionFlow:Learning Implicit Motion Flow for Complex Camera Trajectory Control in Video Generation
Guojun Lei, Chi Wang, Yikai Wang +3
Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are pre…