5 papers
ElasticDiT: Efficient Diffusion Transformers via Elastic Architecture and Sparse Attention for High-Resolution Image Generation on Mobile Devices
Kunpeng Du, Haizhen Xie, Sen Lu +11
The Diffusion Transformer (DiT) architecture is the state-of-the-art paradigm for high-fidelity image generation, underpinning models like Stable Diffusion-3 and FLUX.1. However, d…
Beyond Textual CoT: Interleaved Text-Image Chains with Deep Confidence Reasoning for Image Editing
Zhentao Zou, Zhengrong Yue, Kunpeng Du +9
Image editing with natural language has gained significant popularity, yet existing methods struggle with intricate object intersections and fine-grained spatial relationships due…
OS-DiffVSR: Towards One-step Latent Diffusion Model for High-detailed Real-world Video Super-Resolution
Hanting Li, Huaao Tang, Jianhong Han +5
Recently, latent diffusion models has demonstrated promising performance in real-world video super-resolution (VSR) task, which can reconstruct high-quality videos from distorted l…
EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution
Haizhen Xie, Kunpeng Du, Qiangyu Yan +5
Utilizing pre-trained Text-to-Image (T2I) diffusion models to guide Blind Super-Resolution (BSR) has become a predominant approach in the field. While T2I models have traditionally…
LIPT: Latency-aware Image Processing Transformer
Junbo Qiao, Wei Li, Haizhen Xie +5
Transformer is leading a trend in the field of image processing. Despite the great success that existing lightweight image processing transformers have achieved, they are tailored…