6 citations · 10 across the 7 of their papers we have counts for
7 papers
ProEdit: Inversion-based Editing From Prompts Done Right
Zhi Ouyang, Dian Zheng, Xiao-Ming Wu +4
Inversion-based visual editing provides an effective and training-free way to edit an image or a video based on user instructions. Existing methods typically inject source image in…
Decoupled Distillation to Erase: A General Unlearning Method for Any Class-centric Tasks
Yu Zhou, Dian Zheng, Qijie Mo +3
In this work, we present DEcoupLEd Distillation To Erase (DELETE), a general and strong unlearning method for any class-centric tasks. To derive this, we first propose a theoretica…
An Economic Framework for 6-DoF Grasp Detection
Xiao-Ming Wu, Jia-Feng Cai, Jian-Jian Jiang +3
Robotic grasping in clutters is a fundamental task in robotic manipulation. In this work, we propose an economic framework for 6-DoF grasp detection, aiming to economize the resour…
Dexterous Grasp Transformer
Guo-Hao Xu, Yi-Lin Wei, Dian Zheng +2
In this work, we propose a novel discriminative framework for dexterous grasp generation, named Dexterous Grasp TRansformer (DGTR), capable of predicting a diverse set of feasible…
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
Dian Zheng, Xiao-Ming Wu, Shuzhou Yang +3
Universal image restoration is a practical and potential computer vision task for real-world applications. The main challenge of this task is handling the different degradation dis…
DiffuVolume: Diffusion Model for Volume based Stereo Matching
Dian Zheng, Xiao-Ming Wu, Zuhao Liu +2
Stereo matching is a significant part in many computer vision tasks and driving-based applications. Recently cost volume-based methods have achieved great success benefiting from t…
Estimator Meets Equilibrium Perspective: A Rectified Straight Through Estimator for Binary Neural Networks Training
Xiao-Ming Wu, Dian Zheng, Zuhao Liu +1
Binarization of neural networks is a dominant paradigm in neural networks compression. The pioneering work BinaryConnect uses Straight Through Estimator (STE) to mimic the gradient…