Search Results for author: Shixiang Tang

Found 29 papers, 10 papers with code

Holistic-Motion2D: Scalable Whole-body Human Motion Generation in 2D Space

no code implementations17 Jun 2024 YuAn Wang, Zhao Wang, Junhao Gong, Di Huang, Tong He, Wanli Ouyang, Jile Jiao, Xuetao Feng, Qi Dou, Shixiang Tang, Dan Xu

In this paper, we introduce a novel path to $\textit{general}$ human motion generation by focusing on 2D space.

MLCM: Multistep Consistency Distillation of Latent Diffusion Model

no code implementations9 Jun 2024 Qingsong Xie, Zhenyi Liao, Chen Chen, Zhijie Deng, Shixiang Tang, Haonan Lu

We further augment MCD with a progressive training strategy to strengthen inter-segment consistency to boost the quality of few-step generations.

Image Generation Style Transfer

DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM

no code implementations19 Mar 2024 Yixuan Wu, Yizhou Wang, Shixiang Tang, Wenhao Wu, Tong He, Wanli Ouyang, Jian Wu, Philip Torr

We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object detection ability of multimodal large language models (MLLMs), such as GPT-4V and Gemini.

Object object-detection +3

Agent3D-Zero: An Agent for Zero-shot 3D Understanding

no code implementations18 Mar 2024 Sha Zhang, Di Huang, Jiajun Deng, Shixiang Tang, Wanli Ouyang, Tong He, Yanyong Zhang

The ability to understand and reason the 3D real world is a crucial milestone towards artificial general intelligence.

Language Modelling Scene Understanding

SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation

no code implementations3 Mar 2024 Hongjian Liu, Qingsong Xie, Zhijie Deng, Chen Chen, Shixiang Tang, Fueyang Fu, Zheng-Jun Zha, Haonan Lu

In contrast to vanilla consistency distillation (CD) which distills the ordinary differential equation solvers-based sampling process of a pretrained teacher model into a student, SCott explores the possibility and validates the efficacy of integrating stochastic differential equation (SDE) solvers into CD to fully unleash the potential of the teacher.

Text-to-Image Generation

A Comprehensive Survey on 3D Content Generation

1 code implementation2 Feb 2024 Jian Liu, Xiaoshui Huang, Tianyu Huang, Lu Chen, Yuenan Hou, Shixiang Tang, Ziwei Liu, Wanli Ouyang, WangMeng Zuo, Junjun Jiang, Xianming Liu

Recent years have witnessed remarkable advances in artificial intelligence generated content(AIGC), with diverse input modalities, e. g., text, image, video, audio and 3D.

LEAD: Exploring Logit Space Evolution for Model Selection

no code implementations CVPR 2024 Zixuan Hu, Xiaotong Li, Shixiang Tang, Jun Liu, Yichun Hu, Ling-Yu Duan

The remarkable success of "pretrain-then-finetune" paradigm has led to a proliferation of available pre-trained models for vision tasks.

Model Selection

Hulk: A Universal Knowledge Translator for Human-Centric Tasks

2 code implementations4 Dec 2023 Yizhou Wang, Yixuan Wu, Shixiang Tang, Weizhen He, Xun Guo, Feng Zhu, Lei Bai, Rui Zhao, Jian Wu, Tong He, Wanli Ouyang

Human-centric perception tasks, e. g., pedestrian detection, skeleton-based action recognition, and pose estimation, have wide industrial applications, such as metaverse and sports analysis.

3D Human Pose Estimation Action Recognition +8

Relation-Aware Distribution Representation Network for Person Clustering with Multiple Modalities

no code implementations1 Aug 2023 Kaijian Liu, Shixiang Tang, Ziyue Li, Zhishuai Li, Lei Bai, Feng Zhu, Rui Zhao

The distribution representation of a clue is a vector consisting of the relation between this clue and all other clues from all modalities, thus being modality agnostic and good for person clustering.

Clustering Relation

MotionGPT: Finetuned LLMs Are General-Purpose Motion Generators

no code implementations19 Jun 2023 Yaqi Zhang, Di Huang, Bin Liu, Shixiang Tang, Yan Lu, Lu Chen, Lei Bai, Qi Chu, Nenghai Yu, Wanli Ouyang

Generating realistic human motion from given action descriptions has experienced significant advancements because of the emerging requirement of digital humans.

Instruct-ReID: A Multi-purpose Person Re-identification Task with Instructions

1 code implementation CVPR 2024 Weizhen He, Yiheng Deng, Shixiang Tang, Qihao Chen, Qingsong Xie, Yizhou Wang, Lei Bai, Feng Zhu, Rui Zhao, Wanli Ouyang, Donglian Qi, Yunfeng Yan

This paper strives to resolve this problem by proposing a new instruct-ReID task that requires the model to retrieve images according to the given image or language instructions.

Person Re-Identification

HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining

1 code implementation CVPR 2023 Shixiang Tang, Cheng Chen, Qingsong Xie, Meilin Chen, Yizhou Wang, Yuanzheng Ci, Lei Bai, Feng Zhu, Haiyang Yang, Li Yi, Rui Zhao, Wanli Ouyang

Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting.

 Ranked #1 on Pedestrian Attribute Recognition on PA-100K (using extra training data)

Attribute Autonomous Driving +5

UniHCP: A Unified Model for Human-Centric Perceptions

1 code implementation CVPR 2023 Yuanzheng Ci, Yizhou Wang, Meilin Chen, Shixiang Tang, Lei Bai, Feng Zhu, Rui Zhao, Fengwei Yu, Donglian Qi, Wanli Ouyang

When adapted to a specific task, UniHCP achieves new SOTAs on a wide range of human-centric tasks, e. g., 69. 8 mIoU on CIHP for human parsing, 86. 18 mA on PA-100K for attribute prediction, 90. 3 mAP on Market1501 for ReID, and 85. 8 JI on CrowdHuman for pedestrian detection, performing better than specialized models tailored for each task.

2D Pose Estimation Attribute +8

Saliency Guided Contrastive Learning on Scene Images

no code implementations22 Feb 2023 Meilin Chen, Yizhou Wang, Shixiang Tang, Feng Zhu, Haiyang Yang, Lei Bai, Rui Zhao, Donglian Qi, Wanli Ouyang

Despite being feasible, recent works largely overlooked discovering the most discriminative regions for contrastive learning to object representations in scene images.

Contrastive Learning Linear evaluation +2

Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains

no code implementations10 May 2022 Haiyang Yang, Meilin Chen, Yizhou Wang, Shixiang Tang, Feng Zhu, Lei Bai, Rui Zhao, Wanli Ouyang

While recent self-supervised learning methods have achieved good performances with evaluation set on the same domain as the training set, they will have an undesirable performance decrease when tested on a different domain.

Self-Supervised Learning

Feature Erasing and Diffusion Network for Occluded Person Re-Identification

1 code implementation CVPR 2022 Zhikang Wang, Feng Zhu, Shixiang Tang, Rui Zhao, Lihuo He, Jiangning Song

With the guidance of the occlusion scores from OEM, the feature diffusion process is mainly conducted on visible body parts, which guarantees the quality of the synthesized NTP characteristics.

 Ranked #1 on Person Re-Identification on Occluded REID (Rank-1 metric)

Person Re-Identification

Mutual CRF-GNN for Few-Shot Learning

no code implementations CVPR 2021 Shixiang Tang, Dapeng Chen, Lei Bai, Kaijian Liu, Yixiao Ge, Wanli Ouyang

In this MCGN, the labels and features of support data are used by the CRF for inferring GNN affinities in a principled and probabilistic way.

Few-Shot Learning

Layerwise Optimization by Gradient Decomposition for Continual Learning

no code implementations CVPR 2021 Shixiang Tang, Dapeng Chen, Jinguo Zhu, Shijie Yu, Wanli Ouyang

The gradient for update should be close to the gradient of the new task, consistent with the gradients shared by all old tasks, and orthogonal to the space spanned by the gradients specific to the old tasks.

Continual Learning

Complementary Relation Contrastive Distillation

1 code implementation CVPR 2021 Jinguo Zhu, Shixiang Tang, Dapeng Chen, Shijie Yu, Yakun Liu, Aijun Yang, Mingzhe Rong, Xiaohua Wang

Specifically, we estimate the mutual relation in an anchor-based way and distill the anchor-student relation under the supervision of its corresponding anchor-teacher relation.

Knowledge Distillation Relation

Gradient Regularized Contrastive Learning for Continual Domain Adaptation

no code implementations23 Mar 2021 Shixiang Tang, Peng Su, Dapeng Chen, Wanli Ouyang

To better understand this issue, we study the problem of continual domain adaptation, where the model is presented with a labelled source domain and a sequence of unlabelled target domains.

Contrastive Learning Domain Adaptation

Gradient Regularized Contrastive Learning for Continual Domain Adaptation

no code implementations25 Jul 2020 Peng Su, Shixiang Tang, Peng Gao, Di Qiu, Ni Zhao, Xiaogang Wang

At the core of our method, gradient regularization plays two key roles: (1) enforces the gradient of contrastive loss not to increase the supervised training loss on the source domain, which maintains the discriminative power of learned features; (2) regularizes the gradient update on the new domain not to increase the classification loss on the old target domains, which enables the model to adapt to an in-coming target domain while preserving the performance of previously observed domains.

Contrastive Learning Domain Adaptation

Continual Representation Learning for Biometric Identification

1 code implementation8 Jun 2020 Bo Zhao, Shixiang Tang, Dapeng Chen, Hakan Bilen, Rui Zhao

With the explosion of digital data in recent years, continuously learning new tasks from a stream of data without forgetting previously acquired knowledge has become increasingly important.

Continual Learning Knowledge Distillation +1

Adapting Object Detectors with Conditional Domain Normalization

no code implementations ECCV 2020 Peng Su, Kun Wang, Xingyu Zeng, Shixiang Tang, Dapeng Chen, Di Qiu, Xiaogang Wang

Then this domain-vector is used to encode the features from another domain through a conditional normalization, resulting in different domains' features carrying the same domain attribute.

3D Object Detection Attribute +2

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