7 papers
MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation
Yang Chen, Xiaowei Xu, Shuai Wang +4
Normalizing Flows (NFs) are powerful generative models capable of exact density estimation and sampling. However, their strict invertibility often forces the model to exhaust its c…
Rethinking Scribble-Guided Image Editing: Generalization, Instruction Adherence, and Multi-Tasking
Mingyi Xu, Jinpeng Lin, Min Zhou +2
Scribble-guided image editing allows users to combine simple scribble annotations with text prompts to specify both where and how an image should be edited, enabling flexible inter…
From Competition to Synergy: Unlocking Reinforcement Learning for Subject-Driven Image Generation
Ziwei Huang, Ying Shu, Hao Fang +5
Subject-driven image generation models face a fundamental trade-off between identity preservation (fidelity) and prompt adherence (editability). While online reinforcement learning…
MCSC-Bench: Multimodal Context-to-Script Creation for Realistic Video Production
Huanran Hu, Zihui Ren, Dingyi Yang +4
Real-world video creation often involves a complex reasoning workflow of selecting relevant shots from noisy materials, planning missing shots for narrative completeness, and organ…
Video Echoed in Music: Semantic, Temporal, and Rhythmic Alignment for Video-to-Music Generation
Xinyi Tong, Yiran Zhu, Jishang Chen +9
Video-to-Music generation seeks to generate musically appropriate background music that enhances audiovisual immersion for videos. However, current approaches suffer from two criti…
RISE-T2V: Rephrasing and Injecting Semantics with LLM for Expansive Text-to-Video Generation
Xiangjun Zhang, Litong Gong, Yinglin Zheng +6
Most text-to-video(T2V) diffusion models depend on pre-trained text encoders for semantic alignment, yet they often fail to maintain video quality when provided with concise prompt…