no code implementations • 4 Apr 2024 • Zijie Wu, Chaohui Yu, Yanqin Jiang, Chenjie Cao, Fan Wang, Xiang Bai
Recent advances in 2D/3D generative models enable the generation of dynamic 3D objects from a single-view video.
no code implementations • 12 Oct 2023 • Zijie Wu, Chaohui Yu, Zhen Zhu, Fan Wang, Xiang Bai
To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper embedding that aligns with the semantic space of the T2I model.
no code implementations • 14 Aug 2023 • Chaohui Yu, Qiang Zhou, Zhibin Wang, Fan Wang
Second, we propose an align-guided contrastive loss to refine the alignment of vision and text embeddings.
no code implementations • 4 Aug 2023 • Qiang Zhou, Chaohui Yu, Jingliang Li, Yuang Liu, Jing Wang, Zhibin Wang
to provide additional consistency constraints, which grows GPU memory consumption and complicates the model's structure and training pipeline.
1 code implementation • 3 Aug 2023 • Qiang Zhou, Chaohui Yu, Shaofeng Zhang, Sitong Wu, Zhibing Wang, Fan Wang
To this end, we propose to extract features corresponding to regional objects as soft prompts for LLM, which provides a straightforward and scalable approach and eliminates the need for LLM fine-tuning.
no code implementations • 27 Jul 2023 • Jingliang Li, Qiang Zhou, Chaohui Yu, Zhengda Lu, Jun Xiao, Zhibin Wang, Fan Wang
To make the constructed volumes as close as possible to the surfaces of objects in the scene and the rendered depth more accurate, we propose to perform depth prediction and radiance field reconstruction simultaneously.
no code implementations • 26 Jul 2023 • Chaohui Yu, Qiang Zhou, Jingliang Li, Zhe Zhang, Zhibin Wang, Fan Wang
To better utilize the sparse 3D points, we propose an efficient point cloud guidance loss to adaptively drive the NeRF's geometry to align with the shape of the sparse 3D points.
no code implementations • 1 Mar 2023 • Qiang Zhou, Chaohui Yu, Zhibin Wang, Fan Wang
In this paper, we propose an end-to-end framework for oriented object detection, which simplifies the model pipeline and obtains superior performance.
no code implementations • CVPR 2023 • Chaohui Yu, Qiang Zhou, Jingliang Li, Jianlong Yuan, Zhibin Wang, Fan Wang
In this work, we propose a novel and data-efficient framework for WILSS, named FMWISS.
no code implementations • 27 Feb 2023 • Qiang Zhou, Yuang Liu, Chaohui Yu, Jingliang Li, Zhibin Wang, Fan Wang
Instead of relabeling each dataset with the unified taxonomy, a category-guided decoding module is designed to dynamically guide predictions to each datasets taxonomy.
no code implementations • 7 Sep 2022 • Qiang Zhou, Chaohui Yu, Hao Luo, Zhibin Wang, Hao Li
Specifically, MimCo takes a pre-trained contrastive learning model as the teacher model and is pre-trained with two types of learning targets: patch-level and image-level reconstruction losses.
no code implementations • 28 May 2022 • Qiang Zhou, Chaohui Yu, Zhibin Wang, Hao Li
To tackle this problem, we propose a purely angle-free framework for rotated object detection, called Point RCNN, which mainly consists of PointRPN and PointReg.
1 code implementation • CVPR 2021 • Qiang Zhou, Chaohui Yu, Zhibin Wang, Qi Qian, Hao Li
To alleviate the confirmation bias problem and improve the quality of pseudo annotations, we further propose a co-rectify scheme based on Instant-Teaching, denoted as Instant-Teaching$^*$.
Ranked #12 on Semi-Supervised Object Detection on COCO 100% labeled data (using extra training data)
no code implementations • 3 Mar 2021 • Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, Tie-Yan Liu
Being expensive and time-consuming to collect massive COVID-19 image samples to train deep classification models, transfer learning is a promising approach by transferring knowledge from the abundant typical pneumonia datasets for COVID-19 image classification.
no code implementations • 28 Jan 2021 • Qiang Zhou, Chaohui Yu, Chunhua Shen, Zhibin Wang, Hao Li
On the COCO dataset, our simple design achieves superior performance compared to both the FCOS baseline detector with NMS post-processing and the recent end-to-end NMS-free detectors.
1 code implementation • 17 Jul 2020 • Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, Tie-Yan Liu
However, it remains challenging to determine which method is suitable for a given application since they are built with certain priors or bias.
no code implementations • 18 Sep 2019 • Chaohui Yu, Jindong Wang, Yiqiang Chen, Meiyu Huang
In this paper, we propose a novel Dynamic Adversarial Adaptation Network (DAAN) to dynamically learn domain-invariant representations while quantitatively evaluate the relative importance of global and local domain distributions.
no code implementations • 22 Jul 2019 • Yiqiang Chen, Jindong Wang, Chaohui Yu, Wen Gao, Xin Qin
It is able to achieve accurate and personalized healthcare without compromising privacy and security.
1 code implementation • 25 Mar 2019 • Chaohui Yu, Jindong Wang, Yiqiang Chen, Zijing Wu
In this paper, we propose a unified Transfer Channel Pruning (TCP) approach for accelerating UDA models.