52 citations · 56 across the 24 of their papers we have counts for
14 papers · 1 filter
DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing
Hanqing Yang, Qiang Zhou, Yongchao Du +6
Recent image editing models have achieved strong visual fidelity but often struggle with tasks requiring complex reasoning. To investigate and enhance the reasoning-grounded planni…
Unified Thinker: A General Reasoning Modular Core for Image Generation
Sashuai Zhou, Qiang Zhou, Jijin Hu +9
Despite impressive progress in high-fidelity image synthesis, generative models still struggle with logic-intensive instruction following, exposing a persistent reasoning--executio…
VC4VG: Optimizing Video Captions for Text-to-Video Generation
Yang Du, Zhuoran Lin, Kaiqiang Song +5
Recent advances in text-to-video (T2V) generation highlight the critical role of high-quality video-text pairs in training models capable of producing coherent and instruction-alig…
Identity-Preserving Image-to-Video Generation via Reward-Guided Optimization
Liao Shen, Wentao Jiang, Yiran Zhu +4
Recent advances in image-to-video (I2V) generation have achieved remarkable progress in synthesizing high-quality, temporally coherent videos from static images. Among all the appl…
Differentiable Solver Search for Fast Diffusion Sampling
Shuai Wang, Zexian Li, Qipeng zhang +5
Diffusion models have demonstrated remarkable generation quality but at the cost of numerous function evaluations. Recently, advanced ODE-based solvers have been developed to mitig…
DMM: Building a Versatile Image Generation Model via Distillation-Based Model Merging
Tianhui Song, Weixin Feng, Shuai Wang +4
The success of text-to-image (T2I) generation models has spurred a proliferation of numerous model checkpoints fine-tuned from the same base model on various specialized datasets.…
PosterMaker: Towards High-Quality Product Poster Generation with Accurate Text Rendering
Yifan Gao, Zihang Lin, Chuanbin Liu +4
Product posters, which integrate subject, scene, and text, are crucial promotional tools for attracting customers. Creating such posters using modern image generation methods is va…
T-Stars-Poster: A Framework for Product-Centric Advertising Image Design
Hongyu Chen, Min Zhou, Jing Jiang +6
Creating advertising images is often a labor-intensive and time-consuming process. Can we automatically generate such images using basic product information like a product foregrou…
FlowDCN: Exploring DCN-like Architectures for Fast Image Generation with Arbitrary Resolution
Shuai Wang, Zexian Li, Tianhui Song +4
Arbitrary-resolution image generation still remains a challenging task in AIGC, as it requires handling varying resolutions and aspect ratios while maintaining high visual quality.…
Enhancing Prompt Following with Visual Control Through Training-Free Mask-Guided Diffusion
Hongyu Chen, Yiqi Gao, Min Zhou +4
Recently, integrating visual controls into text-to-image~(T2I) models, such as ControlNet method, has received significant attention for finer control capabilities. While various t…
RHanDS: Refining Malformed Hands for Generated Images with Decoupled Structure and Style Guidance
Chengrui Wang, Pengfei Liu, Min Zhou +4
Although diffusion models can generate high-quality human images, their applications are limited by the instability in generating hands with correct structures. In this paper, we i…
Accelerating Image Generation with Sub-path Linear Approximation Model
Chen Xu, Tianhui Song, Weixin Feng +4
Diffusion models have significantly advanced the state of the art in image, audio, and video generation tasks. However, their applications in practical scenarios are hindered by sl…
Tuning-Free Noise Rectification for High Fidelity Image-to-Video Generation
Weijie Li, Litong Gong, Yiran Zhu +4
Image-to-video (I2V) generation tasks always suffer from keeping high fidelity in the open domains. Traditional image animation techniques primarily focus on specific domains such…
AtomoVideo: High Fidelity Image-to-Video Generation
Litong Gong, Yiran Zhu, Weijie Li +4
Recently, video generation has achieved significant rapid development based on superior text-to-image generation techniques. In this work, we propose a high fidelity framework for…