Search Results for author: Guansong Lu

Found 10 papers, 5 papers with code

Boosting Text-to-Image Diffusion Models with Fine-Grained Semantic Rewards

1 code implementation31 May 2023 Guian Fang, Zutao Jiang, Jianhua Han, Guansong Lu, Hang Xu, Xiaodan Liang

In this paper, we propose FineRewards to improve the alignment between text and images in text-to-image diffusion models by introducing two new fine-grained semantic rewards: the caption reward and the Semantic Segment Anything (SAM) reward.

Language Modelling Semantic Similarity +1

Entity-Level Text-Guided Image Manipulation

no code implementations22 Feb 2023 Yikai Wang, Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Wei zhang, Yanwei Fu

In the image manipulation phase, SeMani adopts a generative model to synthesize new images conditioned on the entity-irrelevant regions and target text descriptions.

Denoising Image Manipulation

ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and Generation

no code implementations CVPR 2022 Jianan Wang, Guansong Lu, Hang Xu, Zhenguo Li, Chunjing Xu, Yanwei Fu

Existing text-guided image manipulation methods aim to modify the appearance of the image or to edit a few objects in a virtual or simple scenario, which is far from practical application.

Image Generation Image Manipulation

FILIP: Fine-grained Interactive Language-Image Pre-Training

no code implementations ICLR 2022 Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, Chunjing Xu

In this paper, we introduce a large-scale Fine-grained Interactive Language-Image Pre-training (FILIP) to achieve finer-level alignment through a cross-modal late interaction mechanism, which uses a token-wise maximum similarity between visual and textual tokens to guide the contrastive objective.

Image Classification Retrieval +2

Towards Generalized Implementation of Wasserstein Distance in GANs

1 code implementation7 Dec 2020 Minkai Xu, Zhiming Zhou, Guansong Lu, Jian Tang, Weinan Zhang, Yong Yu

Wasserstein GANs (WGANs), built upon the Kantorovich-Rubinstein (KR) duality of Wasserstein distance, is one of the most theoretically sound GAN models.

Guiding the One-to-one Mapping in CycleGAN via Optimal Transport

no code implementations15 Nov 2018 Guansong Lu, Zhiming Zhou, Yuxuan Song, Kan Ren, Yong Yu

CycleGAN is capable of learning a one-to-one mapping between two data distributions without paired examples, achieving the task of unsupervised data translation.


Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer

1 code implementation CVPR 2018 Hao-Shu Fang, Guansong Lu, Xiaolin Fang, Jianwen Xie, Yu-Wing Tai, Cewu Lu

In this paper, we present a novel method to generate synthetic human part segmentation data using easily-obtained human keypoint annotations.

Ranked #4 on Human Part Segmentation on PASCAL-Part (using extra training data)

Human Parsing Human Part Segmentation +2

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