no code implementations • 7 May 2024 • Ruiyang Qin, Zheyu Yan, Dewen Zeng, Zhenge Jia, Dancheng Liu, Jianbo Liu, Zhi Zheng, Ningyuan Cao, Kai Ni, JinJun Xiong, Yiyu Shi
Large Language Models (LLMs) deployed on edge devices learn through fine-tuning and updating a certain portion of their parameters.
no code implementations • 19 Feb 2023 • Haixu Long, Xiaolin Zhang, Yanbin Liu, Zongtai Luo, Jianbo Liu
In this paper, we try to look into the root cause of the LTR task, i. e., training samples for each class are greatly imbalanced, and propose a straightforward solution.
no code implementations • 18 Jan 2023 • Jiawei Zhang, Jinshan Pan, Daoye Wang, Shangchen Zhou, Xing Wei, Furong Zhao, Jianbo Liu, Jimmy Ren
In this paper, we explore optical flow to remove dynamic scene blur by using the multi-scale spatially variant recurrent neural network (RNN).
no code implementations • ICCV 2023 • Aojun Zhou, Yang Li, Zipeng Qin, Jianbo Liu, Junting Pan, Renrui Zhang, Rui Zhao, Peng Gao, Hongsheng Li
In this paper, we aim to reduce model complexity from large vision transformers pretrained by MAE with assistant of sparse training.
2 code implementations • 30 Aug 2022 • Prince Grover, Julia Xu, Justin Tittelfitz, Anqi Cheng, Zheng Li, Jakub Zablocki, Jianbo Liu, Hao Zhou
Standardized datasets and benchmarks have spurred innovations in computer vision, natural language processing, multi-modal and tabular settings.
no code implementations • 11 Jan 2022 • Zipeng Qin, Jianbo Liu, Xiaolin Zhang, Maoqing Tian, Aojun Zhou, Shuai Yi, Hongsheng Li
The recently proposed MaskFormer gives a refreshed perspective on the task of semantic segmentation: it shifts from the popular pixel-level classification paradigm to a mask-level classification method.
1 code implementation • ICCV 2021 • Ziniu Wan, Zhengjia Li, Maoqing Tian, Jianbo Liu, Shuai Yi, Hongsheng Li
To this end, we propose Multi-level Attention Encoder-Decoder Network (MAED), including a Spatial-Temporal Encoder (STE) and a Kinematic Topology Decoder (KTD) to model multi-level attentions in a unified framework.
Ranked #40 on 3D Human Pose Estimation on MPI-INF-3DHP
no code implementations • 25 Jun 2021 • Jianbo Liu, Ying Wang, Shiming Xiang, Chunhong Pan
Previous methods for skeleton-based gesture recognition mostly arrange the skeleton sequence into a pseudo picture or spatial-temporal graph and apply deep Convolutional Neural Network (CNN) or Graph Convolutional Network (GCN) for feature extraction.
4 code implementations • ICLR 2021 • Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang, Kun Yuan, Wenxiu Sun, Hongsheng Li
In this paper, we are the first to study training from scratch an N:M fine-grained structured sparse network, which can maintain the advantages of both unstructured fine-grained sparsity and structured coarse-grained sparsity simultaneously on specifically designed GPUs.
no code implementations • 18 Dec 2020 • Jianbo Liu, Sijie Ren, Yuanjie Zheng, Xiaogang Wang, Hongsheng Li
With the proposed holistically-guided decoder, we implement the EfficientFCN architecture for semantic segmentation and HGD-FPN for object detection and instance segmentation.
no code implementations • ECCV 2020 • Jianbo Liu, Junjun He, Jiawei Zhang, Jimmy S. Ren, Hongsheng Li
State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (dilatedFCN), which adopt dilated convolutions in the backbone networks to extract high-resolution feature maps for achieving high-performance segmentation performance.
no code implementations • CVPR 2020 • Jianbo Liu, Yongcheng Liu, Ying Wang, Veronique Prinet, Shiming Xiang, Chunhong Pan
In this paper, we propose to decouple the gesture into hand posture variations and hand movements, which are then modeled separately.
no code implementations • ECCV 2020 • Jianbo Liu, Junjun He, Jimmy S. Ren, Yu Qiao, Hongsheng Li
Long-range contextual information is essential for achieving high-performance semantic segmentation.
1 code implementation • 5 May 2018 • Yicun Liu, Jimmy Ren, Jianbo Liu, Jiawei Zhang, Xiaohao Chen
Artistic style transfer can be thought as a process to generate different versions of abstraction of the original image.
1 code implementation • CVPR 2018 • Yue Luo, Jimmy Ren, Zhouxia Wang, Wenxiu Sun, Jinshan Pan, Jianbo Liu, Jiahao Pang, Liang Lin
Such suboptimal results are mainly attributed to the inability of imposing sequential geometric consistency, handling severe image quality degradation (e. g. motion blur and occlusion) as well as the inability of capturing the temporal correlation among video frames.
Ranked #3 on Pose Estimation on J-HMDB
no code implementations • 30 May 2017 • Jimmy Ren, ZHIYANG YU, Jianbo Liu, Rui Zhang, Wenxiu Sun, Jiahao Pang, Xiaohao Chen, Qiong Yan
Recent advances in visual tracking showed that deep Convolutional Neural Networks (CNN) trained for image classification can be strong feature extractors for discriminative trackers.
2 code implementations • CVPR 2017 • Jimmy Ren, Xiaohao Chen, Jianbo Liu, Wenxiu Sun, Jiahao Pang, Qiong Yan, Yu-Wing Tai, Li Xu
In this paper, we proposed a novel single stage end-to-end trainable object detection network to overcome this limitation.