Search Results for author: Liang Peng

Found 26 papers, 16 papers with code

LoRA-Composer: Leveraging Low-Rank Adaptation for Multi-Concept Customization in Training-Free Diffusion Models

1 code implementation18 Mar 2024 Yang Yang, Wen Wang, Liang Peng, Chaotian Song, Yao Chen, Hengjia Li, Xiaolong Yang, Qinglin Lu, Deng Cai, Boxi Wu, Wei Liu

Customization generation techniques have significantly advanced the synthesis of specific concepts across varied contexts.

VastTrack: Vast Category Visual Object Tracking

1 code implementation6 Mar 2024 Liang Peng, Junyuan Gao, Xinran Liu, Weihong Li, Shaohua Dong, Zhipeng Zhang, Heng Fan, Libo Zhang

The rich annotations of VastTrack enables development of both the vision-only and the vision-language tracking.

Object Visual Object Tracking +1

MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning

no code implementations22 Dec 2023 Liang Peng, Songyue Cai, Zongqian Wu, Huifang Shang, Xiaofeng Zhu, Xiaoxiao Li

Nonetheless, applying existing prompt learning methods for the diagnosis of neurological disorder still suffers from two issues: (i) existing methods typically treat all patches equally, despite the fact that only a small number of patches in neuroimaging are relevant to the disease, and (ii) they ignore the structural information inherent in the brain connection network which is crucial for understanding and diagnosing neurological disorders.

Semantic Similarity Semantic Textual Similarity

Regulating Intermediate 3D Features for Vision-Centric Autonomous Driving

1 code implementation19 Dec 2023 Junkai Xu, Liang Peng, Haoran Cheng, Linxuan Xia, Qi Zhou, Dan Deng, Wei Qian, Wenxiao Wang, Deng Cai

To resolve this problem, we propose to regulate intermediate dense 3D features with the help of volume rendering.

Autonomous Driving

SmoothVideo: Smooth Video Synthesis with Noise Constraints on Diffusion Models for One-shot Video Tuning

1 code implementation29 Nov 2023 Liang Peng, Haoran Cheng, Zheng Yang, Ruisi Zhao, Linxuan Xia, Chaotian Song, Qinglin Lu, Boxi Wu, Wei Liu

By applying the loss to existing one-shot video tuning methods, we significantly improve the overall consistency and smoothness of the generated videos.

MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection

1 code implementation ICCV 2023 Junkai Xu, Liang Peng, Haoran Cheng, Hao Li, Wei Qian, Ke Li, Wenxiao Wang, Deng Cai

To the best of our knowledge, this work is the first to introduce volume rendering for M3D, and demonstrates the potential of implicit reconstruction for image-based 3D perception.

Monocular 3D Object Detection Object +1

Unsupervised Multiplex Graph Learning with Complementary and Consistent Information

1 code implementation3 Aug 2023 Liang Peng, Xin Wang, Xiaofeng Zhu

Unsupervised multiplex graph learning (UMGL) has been shown to achieve significant effectiveness for different downstream tasks by exploring both complementary information and consistent information among multiple graphs.

Graph Learning Representation Learning

Boosting Semi-Supervised 3D Object Detection with Semi-Sampling

no code implementations14 Nov 2022 Xiaopei Wu, Yang Zhao, Liang Peng, Hua Chen, Xiaoshui Huang, Binbin Lin, Haifeng Liu, Deng Cai, Wanli Ouyang

When training a teacher-student semi-supervised framework, we randomly select gt samples and pseudo samples to both labeled frames and unlabeled frames, making a strong data augmentation for them.

3D Object Detection Data Augmentation +2

SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving

1 code implementation8 Nov 2022 Liang Peng, Boqi Li, Wenhao Yu, Kai Yang, Wenbo Shao, Hong Wang

Therefore, this paper proposes the "Self-Surveillance and Self-Adaption System" as a systematic approach to online minimize the SOTIF risk, which aims to provide a systematic solution for monitoring, quantification, and mitigation of inherent and external risks.

Autonomous Driving Decision Making

PeSOTIF: a Challenging Visual Dataset for Perception SOTIF Problems in Long-tail Traffic Scenarios

1 code implementation7 Nov 2022 Liang Peng, Jun Li, Wenbo Shao, Hong Wang

Perception algorithms in autonomous driving systems confront great challenges in long-tail traffic scenarios, where the problems of Safety of the Intended Functionality (SOTIF) could be triggered by the algorithm performance insufficiencies and dynamic operational environment.

Autonomous Driving object-detection +1

DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection

1 code implementation18 Jul 2022 Liang Peng, Xiaopei Wu, Zheng Yang, Haifeng Liu, Deng Cai

Therefore, we propose to reformulate the instance depth to the combination of the instance visual surface depth (visual depth) and the instance attribute depth (attribute depth).

Attribute Data Augmentation +4

Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completion

1 code implementation CVPR 2022 Xiaopei Wu, Liang Peng, Honghui Yang, Liang Xie, Chenxi Huang, Chengqi Deng, Haifeng Liu, Deng Cai

Many multi-modal methods are proposed to alleviate this issue, while different representations of images and point clouds make it difficult to fuse them, resulting in suboptimal performance.

3D Object Detection Data Augmentation +3

GATE: Graph CCA for Temporal SElf-supervised Learning for Label-efficient fMRI Analysis

1 code implementation17 Mar 2022 Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, Xiaoxiao Li

To improve fMRI representation learning and classification under a label-efficient setting, we propose a novel and theory-driven self-supervised learning (SSL) framework on GCNs, namely Graph CCA for Temporal self-supervised learning on fMRI analysis GATE.

Classification Representation Learning +1

WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection

1 code implementation ICLR 2022 Liang Peng, Senbo Yan, Boxi Wu, Zheng Yang, Xiaofei He, Deng Cai

This network is learned by minimizing our newly-proposed 3D alignment loss between the 3D box estimates and the corresponding RoI LiDAR points.

Monocular 3D Object Detection Object +2

Digging Into Output Representation for Monocular 3D Object Detection

no code implementations29 Sep 2021 Liang Peng, Senbo Yan, Chenxi Huang, Xiaofei He, Deng Cai

This characteristic indicates that monocular 3D detection is inherently different from other typical detection tasks that have the same dimensional input and output.

Monocular 3D Object Detection Object +1

Multi-level Feature Learning for Contrastive Multi-view Clustering

1 code implementation CVPR 2022 Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He

Our method learns different levels of features from the raw features, including low-level features, high-level features, and semantic labels/features in a fusion-free manner, so that it can effectively achieve the reconstruction objective and the consistency objectives in different feature spaces.

Clustering Contrastive Learning

Lidar Point Cloud Guided Monocular 3D Object Detection

1 code implementation19 Apr 2021 Liang Peng, Fei Liu, Zhengxu Yu, Senbo Yan, Dan Deng, Zheng Yang, Haifeng Liu, Deng Cai

We delve into this underlying mechanism and then empirically find that: concerning the label accuracy, the 3D location part in the label is preferred compared to other parts of labels.

Monocular 3D Object Detection Object +1

OCM3D: Object-Centric Monocular 3D Object Detection

no code implementations13 Apr 2021 Liang Peng, Fei Liu, Senbo Yan, Xiaofei He, Deng Cai

Image-only and pseudo-LiDAR representations are commonly used for monocular 3D object detection.

Monocular 3D Object Detection Object +1

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