3 citations · 4 across the 9 of their papers we have counts for
10 papers
Unveiling the Secret of AdaLN-Zero in Diffusion Transformer
Jie Zhu, Mingyu Ding, Boqiang Duan +2
Diffusion transformer (DiT), a rapidly emerging architecture for image generation, has gained much attention. However, despite ongoing efforts to improve its performance, the under…
LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV
Tengfei Liu, Yang Shi, Xuanyu Zhu +17
Audio-visual generation is rapidly advancing from short clips to minute-long content, while existing evaluation protocols remain largely confined to short-form settings. Existing b…
A Simple Baseline for Unifying Understanding, Generation, and Editing via Vanilla Next-token Prediction
Jie Zhu, Hanghang Ma, Jia Wang +6
In this work, we introduce Wallaroo, a simple autoregressive baseline that leverages next-token prediction to unify multi-modal understanding, image generation, and editing at the…
Auditing Data Provenance in Real-world Text-to-Image Diffusion Models for Privacy and Copyright Protection
Jie Zhu, Leye Wang
Text-to-image diffusion model since its propose has significantly influenced the content creation due to its impressive generation capability. However, this capability depends on l…
A Unified and Scalable Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability
Jie Zhu, Jirong Zha, Ding Li +1
Self-supervised learning shows promise in harnessing extensive unlabeled data, but it also confronts significant privacy concerns, especially in vision. In this paper, we perform m…
MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts
Jie Zhu, Yixiong Chen, Mingyu Ding +3
Text-to-image diffusion has attracted vast attention due to its impressive image-generation capabilities. However, when it comes to human-centric text-to-image generation, particul…
Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment
Jie Zhu, Leye Wang, Xiao Han +2
The size of deep learning models in artificial intelligence (AI) software is increasing rapidly, hindering the large-scale deployment on resource-restricted devices (e.g., smartpho…
Understanding Self-Supervised Pretraining with Part-Aware Representation Learning
Jie Zhu, Jiyang Qi, Mingyu Ding +6
In this paper, we are interested in understanding self-supervised pretraining through studying the capability that self-supervised representation pretraining methods learn part-awa…
MSP : Refine Boundary Segmentation via Multiscale Superpixel
Jie Zhu, Huabin Huang, Banghuai Li +2
In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges…
E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation
Jie Zhu, Huabin Huang, Banghuai Li +1
Modern semantic segmentation methods devote much effect to adjusting image feature representations to improve the segmentation performance in various ways, such as architecture des…