collaborators

6 papers

cs.CV2025

ReasonEdit: Towards Reasoning-Enhanced Image Editing Models

Fukun Yin, Shiyu Liu, Yucheng Han +12

Recent advances in image editing models have shown remarkable progress. A common architectural design couples a multimodal large language model (MLLM) encoder with a diffusion deco…

cs.CV2025

RegionE: Adaptive Region-Aware Generation for Efficient Image Editing

Pengtao Chen, Xianfang Zeng, Maosen Zhao +7

Recently, instruction-based image editing (IIE) has received widespread attention. In practice, IIE often modifies only specific regions of an image, while the remaining areas larg…

cs.CV2025

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Pengtao Chen, Xianfang Zeng, Maosen Zhao +5

While Diffusion Transformers (DiTs) have achieved breakthroughs in video generation, this long sequence generation task remains constrained by the quadratic complexity of attention…

cs.LG2025

Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning

Maosen Zhao, Pengtao Chen, Chong Yu +3

Model quantization reduces the bit-width of weights and activations, improving memory efficiency and inference speed in diffusion models. However, achieving 4-bit quantization rema…

cs.CV2025

DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Hanling Zhang, Rundong Su, Zhihang Yuan +5

Text-to-image generation models, especially Multimodal Diffusion Transformers (MMDiT), have shown remarkable progress in generating high-quality images. However, these models often…

cs.CV2025

FAVOR-Bench: A Comprehensive Benchmark for Fine-Grained Video Motion Understanding

Chongjun Tu, Lin Zhang, Pengtao Chen +5

Multimodal Large Language Models (MLLMs) have shown remarkable capabilities in video content understanding but still struggle with fine-grained motion comprehension. To comprehensi…