Search Results for author: Zhaoxiang Zhang

Found 33 papers, 20 papers with code

Pro-tuning: Unified Prompt Tuning for Vision Tasks

no code implementations28 Jul 2022 Xing Nie, Bolin Ni, Jianlong Chang, Gaomeng Meng, Chunlei Huo, Zhaoxiang Zhang, Shiming Xiang, Qi Tian, Chunhong Pan

To this end, we propose parameter-efficient Prompt tuning (Pro-tuning) to adapt frozen vision models to various downstream vision tasks.

Adversarial Robustness Image Classification +4

Fully Sparse 3D Object Detection

1 code implementation20 Jul 2022 Lue Fan, Feng Wang, Naiyan Wang, Zhaoxiang Zhang

To enable efficient long-range LiDAR-based object detection, we build a fully sparse 3D object detector (FSD).

3D Object Detection Autonomous Driving +1

Densely Constrained Depth Estimator for Monocular 3D Object Detection

1 code implementation20 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.

Depth Estimation Graph Matching +2

Implicit Sample Extension for Unsupervised Person Re-Identification

1 code implementation CVPR 2022 Xinyu Zhang, Dongdong Li, Zhigang Wang, Jian Wang, Errui Ding, Javen Qinfeng Shi, Zhaoxiang Zhang, Jingdong Wang

Specifically, we generate support samples from actual samples and their neighbouring clusters in the embedding space through a progressive linear interpolation (PLI) strategy.

Unsupervised Person Re-Identification

HP-Capsule: Unsupervised Face Part Discovery by Hierarchical Parsing Capsule Network

no code implementations CVPR 2022 Chang Yu, Xiangyu Zhu, Xiaomei Zhang, Zidu Wang, Zhaoxiang Zhang, Zhen Lei

Capsule networks are designed to present the objects by a set of parts and their relationships, which provide an insight into the procedure of visual perception.

DATA: Domain-Aware and Task-Aware Self-supervised Learning

1 code implementation CVPR 2022 Qing Chang, Junran Peng, Lingxie Xie, Jiajun Sun, Haoran Yin, Qi Tian, Zhaoxiang Zhang

However, due to the high training costs and the unconsciousness of downstream usages, most self-supervised learning methods lack the capability to correspond to the diversities of downstream scenarios, as there are various data domains, different vision tasks and latency constraints on models.

Image Classification Model Selection +5

The Devil Is in the Details: Window-based Attention for Image Compression

1 code implementation CVPR 2022 Renjie Zou, Chunfeng Song, Zhaoxiang Zhang

Inspired by recent progresses of Vision Transformer (ViT) and Swin Transformer, we found that combining the local-aware attention mechanism with the global-related feature learning could meet the expectation in image compression.

Image Compression

Emergence of Machine Language: Towards Symbolic Intelligence with Neural Networks

no code implementations14 Jan 2022 Yuqi Wang, Xu-Yao Zhang, Cheng-Lin Liu, Zhaoxiang Zhang

Moreover, through experiments we show that discrete language representation has several advantages compared with continuous feature representation, from the aspects of interpretability, generalization, and robustness.

Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer

no code implementations CVPR 2022 Wenjian Wang, Lijuan Duan, Yuxi Wang, Qing En, Junsong Fan, Zhaoxiang Zhang

To remedy this problem, we propose an interesting and challenging cross-domain few-shot semantic segmentation task, where the training and test tasks perform on different domains.

Contrastive Learning Cross-Domain Few-Shot +2

Continual Stereo Matching of Continuous Driving Scenes With Growing Architecture

1 code implementation CVPR 2022 Chenghao Zhang, Kun Tian, Bin Fan, Gaofeng Meng, Zhaoxiang Zhang, Chunhong Pan

The deep stereo models have achieved state-of-the-art performance on driving scenes, but they suffer from severe performance degradation when tested on unseen scenes.

Continual Learning Stereo Matching

Embracing Single Stride 3D Object Detector with Sparse Transformer

1 code implementation CVPR 2022 Lue Fan, Ziqi Pang, Tianyuan Zhang, Yu-Xiong Wang, Hang Zhao, Feng Wang, Naiyan Wang, Zhaoxiang Zhang

In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to input scene size is significantly smaller compared to 2D detection cases.

3D Object Detection Autonomous Driving +2

Immortal Tracker: Tracklet Never Dies

1 code implementation26 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.

3D Multi-Object Tracking Trajectory Prediction


no code implementations ICLR 2022 Qu Tang, Xiangyu Zhu, Zhen Lei, Zhaoxiang Zhang

In this paper, we work on object dynamics and propose Object Dynamics Distillation Network (ODDN), a framework that distillates explicit object dynamics (e. g., velocity) from sequential static representations.

Predict Future Video Frames Video Understanding

GAIA: A Transfer Learning System of Object Detection that Fits Your Needs

1 code implementation CVPR 2021 Xingyuan Bu, Junran Peng, Junjie Yan, Tieniu Tan, Zhaoxiang Zhang

Transfer learning with pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently.

Natural Language Processing object-detection +2

Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness

1 code implementation28 Apr 2021 Manyu Zhu, Dongliang He, Xin Li, Chao Li, Fu Li, Xiao Liu, Errui Ding, Zhaoxiang Zhang

Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial.

Image Inpainting

Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy

1 code implementation CVPR 2021 Zikai Zhang, Bineng Zhong, Shengping Zhang, Zhenjun Tang, Xin Liu, Zhaoxiang Zhang

A practical long-term tracker typically contains three key properties, i. e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness mechanism.

Multiple Object Tracking Philosophy

RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features

1 code implementation CVPR 2021 Gang Zhang, Xin Lu, Jingru Tan, Jianmin Li, Zhaoxiang Zhang, Quanquan Li, Xiaolin Hu

In this work, we propose a new method called RefineMask for high-quality instance segmentation of objects and scenes, which incorporates fine-grained features during the instance-wise segmenting process in a multi-stage manner.

Instance Segmentation Semantic Segmentation

Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression

1 code implementation CVPR 2021 Zigang Geng, Ke Sun, Bin Xiao, Zhaoxiang Zhang, Jingdong Wang

Our motivation is that regressing keypoint positions accurately needs to learn representations that focus on the keypoint regions.

Keypoint Detection

RangeDet:In Defense of Range View for LiDAR-based 3D Object Detection

1 code implementation18 Mar 2021 Lue Fan, Xuan Xiong, Feng Wang, Naiyan Wang, Zhaoxiang Zhang

The most notable difference with previous works is that our method is purely based on the range view representation.

3D Object Detection object-detection +2

Clothing Status Awareness for Long-Term Person Re-Identification

no code implementations ICCV 2021 Yan Huang, Qiang Wu, Jingsong Xu, Yi Zhong, Zhaoxiang Zhang

This work argues that these approaches in fact are not aware of clothing status (i. e., change or no-change) of a pedestrian.

Person Re-Identification

Uncertainty-Aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation

no code implementations ICCV 2021 Yuxi Wang, Junran Peng, Zhaoxiang Zhang

Unsupervised domain adaptation for semantic segmentation aims to assign the pixel-level labels for unlabeled target domain by transferring knowledge from the labeled source domain.

Self-Supervised Learning Semantic Segmentation +1

RangeDet: In Defense of Range View for LiDAR-Based 3D Object Detection

1 code implementation ICCV 2021 Lue Fan, Xuan Xiong, Feng Wang, Naiyan Wang, Zhaoxiang Zhang

We first analyze the existing range-view-based methods and find two issues overlooked by previous works: 1) the scale variation between nearby and far away objects; 2) the inconsistency between the 2D range image coordinates used in feature extraction and the 3D Cartesian coordinates used in output.

3D Object Detection object-detection +2

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

1 code implementation9 Dec 2020 Xueyi Li, Tianfei Zhou, Jianwu Li, Yi Zhou, Zhaoxiang Zhang

We formulate WSSS as a novel group-wise learning task that explicitly models semantic dependencies in a group of images to estimate more reliable pseudo ground-truths, which can be used for training more accurate segmentation models.

Ranked #21 on Weakly-Supervised Semantic Segmentation on COCO 2014 val (using extra training data)

Structured Prediction Weakly-Supervised Semantic Segmentation

Unsupervised Object Detection with LiDAR Clues

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.

object-detection Object Detection

Manual-Label Free 3D Detection via An Open-Source Simulator

no code implementations16 Nov 2020 Zhen Yang, Chi Zhang, Huiming Guo, Zhaoxiang Zhang

In this paper, we propose a manual-label free 3D detection algorithm that leverages the CARLA simulator to generate a large amount of self-labeled training samples and introduces a novel Domain Adaptive VoxelNet (DA-VoxelNet) that can cross the distribution gap from the synthetic data to the real scenario.

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