3 code implementations • 18 Mar 2024 • Hongbo Zhao, Bolin Ni, Haochen Wang, Junsong Fan, Fei Zhu, Yuxi Wang, Yuntao Chen, Gaofeng Meng, Zhaoxiang Zhang
(i) For unwanted knowledge, efficient and effective deleting is crucial.
1 code implementation • 18 Jan 2024 • Changyao Tian, Xizhou Zhu, Yuwen Xiong, Weiyun Wang, Zhe Chen, Wenhai Wang, Yuntao Chen, Lewei Lu, Tong Lu, Jie zhou, Hongsheng Li, Yu Qiao, Jifeng Dai
Developing generative models for interleaved image-text data has both research and practical value.
1 code implementation • 11 Jan 2024 • Yuwen Xiong, Zhiqi Li, Yuntao Chen, Feng Wang, Xizhou Zhu, Jiapeng Luo, Wenhai Wang, Tong Lu, Hongsheng Li, Yu Qiao, Lewei Lu, Jie zhou, Jifeng Dai
The advancements in speed and efficiency of DCNv4, combined with its robust performance across diverse vision tasks, show its potential as a foundational building block for future vision models.
1 code implementation • 29 Nov 2023 • Yuqi Wang, JiaWei He, Lue Fan, Hongxin Li, Yuntao Chen, Zhaoxiang Zhang
In autonomous driving, predicting future events in advance and evaluating the foreseeable risks empowers autonomous vehicles to better plan their actions, enhancing safety and efficiency on the road.
1 code implementation • 16 Jun 2023 • Yuqi Wang, Yuntao Chen, Xingyu Liao, Lue Fan, Zhaoxiang Zhang
In this work, we address this limitation by studying camera-based 3D panoptic segmentation, aiming to achieve a unified occupancy representation for camera-only 3D scene understanding.
no code implementations • 8 Jun 2023 • JiaWei He, Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang
We devise the DoubleClustering algorithm to obtain object clusters from reconstructed scene-level points, and further enhance the model's detection capabilities by developing three stages of generalization: progressing from complete to partial, static to dynamic, and close to distant.
no code implementations • 8 Jun 2023 • JiaWei He, Lue Fan, Yuqi Wang, Yuntao Chen, Zehao Huang, Naiyan Wang, Zhaoxiang Zhang
In this paper, we rethink the data association in 2D MOT and utilize the 3D object representation to separate each object in the feature space.
1 code implementation • 25 May 2023 • Xizhou Zhu, Yuntao Chen, Hao Tian, Chenxin Tao, Weijie Su, Chenyu Yang, Gao Huang, Bin Li, Lewei Lu, Xiaogang Wang, Yu Qiao, Zhaoxiang Zhang, Jifeng Dai
These agents, equipped with the logic and common sense capabilities of LLMs, can skillfully navigate complex, sparse-reward environments with text-based interactions.
no code implementations • 22 May 2023 • Jinglin Zhan, Tiejun Liu, RenGang Li, Jingwei Zhang, Zhaoxiang Zhang, Yuntao Chen
Data and model are the undoubtable two supporting pillars for LiDAR object detection.
1 code implementation • 24 Apr 2023 • Yingyan Li, Lue Fan, Yang Liu, Zehao Huang, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
In this paper, we study how to effectively leverage image modality in the emerging fully sparse architecture.
2 code implementations • ICCV 2023 • Lue Fan, Yuxue Yang, Yiming Mao, Feng Wang, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
Drawing inspiration from this, we propose a high-performance offline detector in a track-centric perspective instead of the conventional object-centric perspective.
1 code implementation • CVPR 2023 • JiaWei He, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
We explore long-term temporal visual correspondence-based optimization for 3D video object detection in this work.
1 code implementation • CVPR 2023 • Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang
The transformation of features from 2D perspective space to 3D space is essential to multi-view 3D object detection.
2 code implementations • CVPR 2023 • Chenyu Yang, Yuntao Chen, Hao Tian, Chenxin Tao, Xizhou Zhu, Zhaoxiang Zhang, Gao Huang, Hongyang Li, Yu Qiao, Lewei Lu, Jie zhou, Jifeng Dai
The proposed method is verified with a wide spectrum of traditional and modern image backbones and achieves new SoTA results on the large-scale nuScenes dataset.
Ranked #5 on 3D Object Detection on Rope3D
1 code implementation • 10 Oct 2022 • Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang
In this paper, we propose 4D unsupervised object discovery, jointly discovering objects from 4D data -- 3D point clouds and 2D RGB images with temporal information.
1 code implementation • 20 Jul 2022 • Yingyan Li, Yuntao Chen, JiaWei He, Zhaoxiang Zhang
So these methods only use a small number of projection constraints and produce insufficient depth candidates, leading to inaccurate depth estimation.
1 code implementation • CVPR 2022 • Jianglong Ye, Yuntao Chen, Naiyan Wang, Xiaolong Wang
This limitation leads to tedious data processing (converting non-watertight raw data to watertight) as well as the incapability of representing general object shapes in the real world.
1 code implementation • 26 Nov 2021 • Qitai Wang, Yuntao Chen, Ziqi Pang, Naiyan Wang, Zhaoxiang Zhang
We employ a simple Kalman filter for trajectory prediction and preserve the tracklet by prediction when the target is not visible.
1 code implementation • 24 Nov 2021 • Jianglong Ye, Yuntao Chen, Naiyan Wang, Xiaolong Wang
Tracking and reconstructing 3D objects from cluttered scenes are the key components for computer vision, robotics and autonomous driving systems.
no code implementations • CVPR 2021 • Hao Tian, Yuntao Chen, Jifeng Dai, Zhaoxiang Zhang, Xizhou Zhu
We further identify another major issue, seldom noticed by the community, that the long-tailed and open-ended (sub-)category distribution should be accommodated.
no code implementations • 5 Aug 2019 • Yuntao Chen, Chenxia Han, Naiyan Wang, Zhao-Xiang Zhang
Recently, one-stage object detectors gain much attention due to their simplicity in practice.
2 code implementations • ICCV 2019 • Haiping Wu, Yuntao Chen, Naiyan Wang, Zhao-Xiang Zhang
In this work, we argue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection.
Ranked #15 on Video Object Detection on ImageNet VID
1 code implementation • 14 Mar 2019 • Yuntao Chen, Chenxia Han, Yanghao Li, Zehao Huang, Yi Jiang, Naiyan Wang, Zhao-Xiang Zhang
A Simple and Versatile Framework for Object Detection and Instance Recognition
4 code implementations • ICCV 2019 • Yanghao Li, Yuntao Chen, Naiyan Wang, Zhao-Xiang Zhang
In this work, we first present a controlled experiment to investigate the effect of receptive fields for scale variation in object detection.
Ranked #90 on Object Detection on COCO test-dev
2 code implementations • ICCV 2019 • Chuanchen Luo, Yuntao Chen, Naiyan Wang, Zhao-Xiang Zhang
With the surge of deep learning techniques, the field of person re-identification has witnessed rapid progress in recent years.
no code implementations • 5 Jul 2017 • Yuntao Chen, Naiyan Wang, Zhao-Xiang Zhang
have shown that the dark knowledge within a powerful teacher model can significantly help the training of a smaller and faster student network.