no code implementations • 29 Dec 2024 • Daiheng Gao, Shilin Lu, Shaw Walters, Wenbo Zhou, Jiaming Chu, Jie Zhang, Bang Zhang, Mengxi Jia, Jian Zhao, Zhaoxin Fan, Weiming Zhang
Removing unwanted concepts from large-scale text-to-image (T2I) diffusion models while maintaining their overall generative quality remains an open challenge.
no code implementations • 23 Jul 2024 • Ke Sun, Jian Cao, Qi Wang, Linrui Tian, Xindi Zhang, Lian Zhuo, Bang Zhang, Liefeng Bo, Wenbo Zhou, Weiming Zhang, Daiheng Gao
Specifically, these models struggle to maintain a balance between control and consistency when generating images for virtual clothing trials.
no code implementations • 27 Feb 2024 • Linrui Tian, Qi Wang, Bang Zhang, Liefeng Bo
In this work, we tackle the challenge of enhancing the realism and expressiveness in talking head video generation by focusing on the dynamic and nuanced relationship between audio cues and facial movements.
1 code implementation • 12 Dec 2023 • Kangneng Zhou, Daiheng Gao, Xuan Wang, Jie Zhang, Peng Zhang, Xusen Sun, Longhao Zhang, Shiqi Yang, Bang Zhang, Liefeng Bo, Yaxing Wang, Ming-Ming Cheng
This enhances masked-based editing in local areas; second, we present a novel distillation strategy: Conditional Distillation on Geometry and Texture (CDGT).
no code implementations • 4 Dec 2023 • Xusen Sun, Longhao Zhang, Hao Zhu, Peng Zhang, Bang Zhang, Xinya Ji, Kangneng Zhou, Daiheng Gao, Liefeng Bo, Xun Cao
Audio-driven talking head generation has drawn much attention in recent years, and many efforts have been made in lip-sync, expressive facial expressions, natural head pose generation, and high video quality.
1 code implementation • CVPR 2024 • Li Hu, Xin Gao, Peng Zhang, Ke Sun, Bang Zhang, Liefeng Bo
Character Animation aims to generating character videos from still images through driving signals.
1 code implementation • ICCV 2023 • Lijun Li, Linrui Tian, Xindi Zhang, Qi Wang, Bang Zhang, Mengyuan Liu, Chen Chen
The current interacting hand (IH) datasets are relatively simplistic in terms of background and texture, with hand joints being annotated by a machine annotator, which may result in inaccuracies, and the diversity of pose distribution is limited.
no code implementations • 8 Aug 2023 • Daiheng Gao, Xu Chen, Xindi Zhang, Qi Wang, Ke Sun, Bang Zhang, Liefeng Bo, QiXing Huang
Since traditional warping-based texture generation methods require a significant number of control points to be manually selected for each type of garment, which can be a time-consuming and tedious process.
no code implementations • 23 May 2023 • Lijun Li, Li'an Zhuo, Bang Zhang, Liefeng Bo, Chen Chen
Hand mesh reconstruction from the monocular image is a challenging task due to its depth ambiguity and severe occlusion, there remains a non-unique mapping between the monocular image and hand mesh.
1 code implementation • 22 May 2023 • Kezhou Lin, Xiaohan Wang, Linchao Zhu, Ke Sun, Bang Zhang, Yi Yang
In this paper, we tackle the problem of sign language translation (SLT) without gloss annotations.
no code implementations • CVPR 2023 • Weichuang Li, Longhao Zhang, Dong Wang, Bin Zhao, Zhigang Wang, Mulin Chen, Bang Zhang, Zhongjian Wang, Liefeng Bo, Xuelong Li
Talking head generation aims to generate faces that maintain the identity information of the source image and imitate the motion of the driving image.
no code implementations • CVPR 2023 • Li’an Zhuo, Jian Cao, Qi Wang, Bang Zhang, Liefeng Bo
Then the optimization-based method is introduced to reconstruct the foot pose and foot-ground contact for the general multi-view datasets including AIST++ and Human3. 6M.
1 code implementation • 14 Oct 2022 • Daiheng Gao, Yuliang Xiu, Kailin Li, Lixin Yang, Feng Wang, Peng Zhang, Bang Zhang, Cewu Lu, Ping Tan
Unity GUI is also provided to generate synthetic hand data with user-defined settings, e. g., pose, camera, background, lighting, textures, and accessories.
no code implementations • 8 Jul 2022 • Yucheng Suo, Zhedong Zheng, Xiaohan Wang, Bang Zhang, Yi Yang
We optimize the two losses and keypoint detector network in an end-to-end manner.
no code implementations • 21 Jun 2022 • Lijun Li, Li'an Zhuo, Bang Zhang
In this work, we introduce our solution to the EPIC-KITCHENS-100 2022 Action Detection challenge.
1 code implementation • CVPR 2022 • Mingxing Li, Li Hu, Zhiwei Xiong, Bang Zhang, Pan Pan, Dong Liu
In this paper, we propose a Recurrent Dynamic Embedding (RDE) to build a memory bank of constant size.
Ranked #16 on Semi-Supervised Video Object Segmentation on MOSE
1 code implementation • CVPR 2022 • Xuanmeng Zhang, Zhedong Zheng, Daiheng Gao, Bang Zhang, Pan Pan, Yi Yang
To address this challenge, we propose Multi-View Consistent Generative Adversarial Networks (MVCGAN) for high-quality 3D-aware image synthesis with geometry constraints.
no code implementations • 1 Jun 2021 • Qianyu Feng, Bang Zhang, Yi Yang
Differently, our goal is to represent a system with a part-whole hierarchy and discover the implied dependencies among intra-system variables: inferring the interactions that possess causal effects on the sub-system behavior with REcurrent partItioned Network (REIN).
1 code implementation • 31 May 2021 • Yuan Gan, Yawei Luo, Xin Yu, Bang Zhang, Yi Yang
In this paper, we investigate the task of hallucinating an authentic high-resolution (HR) human face from multiple low-resolution (LR) video snapshots.
no code implementations • 2 May 2021 • Qianyu Feng, Linchao Zhu, Bang Zhang, Pan Pan, Yi Yang
Specifically, we expect to approximate the real joint distribution over the partial observation and latent variables, thus infer the unseen targets respectively.
no code implementations • CVPR 2021 • Li Hu, Peng Zhang, Bang Zhang, Pan Pan, Yinghui Xu, Rong Jin
To address this limitation, we propose to Learn position and target Consistency framework for Memory-based video object segmentation, termed as LCM.
no code implementations • CVPR 2014 • Bang Zhang, Yi Wang, Yang Wang, Fang Chen
Many prevalent multi-class classification approaches can be unified and generalized by the output coding framework which usually consists of three phases: (1) coding, (2) learning binary classifiers, and (3) decoding.