30 citations · 113 across the 35 of their papers we have counts for
12 papers · 1 filter
One More Step: A Versatile Plug-and-Play Module for Rectifying Diffusion Schedule Flaws and Enhancing Low-Frequency Controls
Minghui Hu, Jianbin Zheng, Chuanxia Zheng +3
It is well known that many open-released foundational diffusion models have difficulty in generating images that substantially depart from average brightness, despite such images b…
Peer is Your Pillar: A Data-unbalanced Conditional GANs for Few-shot Image Generation
Ziqiang Li, Chaoyue Wang, Xue Rui +3
Few-shot image generation aims to train generative models using a small number of training images. When there are few images available for training (e.g. 10 images), Learning From…
HandRefiner: Refining Malformed Hands in Generated Images by Diffusion-based Conditional Inpainting
Wenquan Lu, Yufei Xu, Jing Zhang +2
Diffusion models have achieved remarkable success in generating realistic images but suffer from generating accurate human hands, such as incorrect finger counts or irregular shape…
Decompose Semantic Shifts for Composed Image Retrieval
Xingyu Yang, Daqing Liu, Heng Zhang +3
Composed image retrieval is a type of image retrieval task where the user provides a reference image as a starting point and specifies a text on how to shift from the starting poin…
Autoregressive Omni-Aware Outpainting for Open-Vocabulary 360-Degree Image Generation
Zhuqiang Lu, Kun Hu, Chaoyue Wang +2
A 360-degree (omni-directional) image provides an all-encompassing spherical view of a scene. Recently, there has been an increasing interest in synthesising 360-degree images from…
Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation
Yiyang Chen, Shanshan Zhao, Changxing Ding +3
In recent years, cross-modal domain adaptation has been studied on the paired 2D image and 3D LiDAR data to ease the labeling costs for 3D LiDAR semantic segmentation (3DLSS) in th…
Cocktail: Mixing Multi-Modality Controls for Text-Conditional Image Generation
Minghui Hu, Jianbin Zheng, Daqing Liu +4
Text-conditional diffusion models are able to generate high-fidelity images with diverse contents. However, linguistic representations frequently exhibit ambiguous descriptions of…
MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis
Jianbin Zheng, Daqing Liu, Chaoyue Wang +4
Existing multimodal conditional image synthesis (MCIS) methods generate images conditioned on any combinations of various modalities that require all of them must be exactly confor…
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation
Liyao Tang, Zhe Chen, Shanshan Zhao +2
Pseudo-labels are widely employed in weakly supervised 3D segmentation tasks where only sparse ground-truth labels are available for learning. Existing methods often rely on empiri…
ESceme: Vision-and-Language Navigation with Episodic Scene Memory
Qi Zheng, Daqing Liu, Chaoyue Wang +3
Vision-and-language navigation (VLN) simulates a visual agent that follows natural-language navigation instructions in real-world scenes. Existing approaches have made enormous pro…
OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System
Chao Xue, Wei Liu, Shuai Xie +25
Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to t…
Eliminating Contextual Prior Bias for Semantic Image Editing via Dual-Cycle Diffusion
Zuopeng Yang, Tianshu Chu, Xin Lin +4
The recent success of text-to-image generation diffusion models has also revolutionized semantic image editing, enabling the manipulation of images based on query/target texts. Des…