Search Results for author: Jianhua Han

Found 18 papers, 1 papers with code

DetGPT: Detect What You Need via Reasoning

no code implementations23 May 2023 Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang

Overall, our proposed paradigm and DetGPT demonstrate the potential for more sophisticated and intuitive interactions between humans and machines.

Autonomous Driving object-detection +1

DetCLIPv2: Scalable Open-Vocabulary Object Detection Pre-training via Word-Region Alignment

no code implementations CVPR 2023 Lewei Yao, Jianhua Han, Xiaodan Liang, Dan Xu, Wei zhang, Zhenguo Li, Hang Xu

This paper presents DetCLIPv2, an efficient and scalable training framework that incorporates large-scale image-text pairs to achieve open-vocabulary object detection (OVD).

Language Modelling object-detection +1

CLIP$^2$: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data

no code implementations22 Mar 2023 Yihan Zeng, Chenhan Jiang, Jiageng Mao, Jianhua Han, Chaoqiang Ye, Qingqiu Huang, Dit-yan Yeung, Zhen Yang, Xiaodan Liang, Hang Xu

Contrastive Language-Image Pre-training, benefiting from large-scale unlabeled text-image pairs, has demonstrated great performance in open-world vision understanding tasks.

Towards Universal Vision-language Omni-supervised Segmentation

no code implementations12 Mar 2023 Bowen Dong, Jiaxi Gu, Jianhua Han, Hang Xu, WangMeng Zuo

To improve the open-world segmentation ability, we leverage omni-supervised data (i. e., panoptic segmentation data, object detection data, and image-text pairs data) into training, thus enriching the open-world segmentation ability and achieving better segmentation accuracy.

Instance Segmentation object-detection +2

CapDet: Unifying Dense Captioning and Open-World Detection Pretraining

no code implementations CVPR 2023 Yanxin Long, Youpeng Wen, Jianhua Han, Hang Xu, Pengzhen Ren, Wei zhang, Shen Zhao, Xiaodan Liang

Besides, our CapDet also achieves state-of-the-art performance on dense captioning tasks, e. g., 15. 44% mAP on VG V1. 2 and 13. 98% on the VG-COCO dataset.

Dense Captioning

Visual Exemplar Driven Task-Prompting for Unified Perception in Autonomous Driving

no code implementations CVPR 2023 Xiwen Liang, Minzhe Niu, Jianhua Han, Hang Xu, Chunjing Xu, Xiaodan Liang

Multi-task learning has emerged as a powerful paradigm to solve a range of tasks simultaneously with good efficiency in both computation resources and inference time.

Autonomous Driving Lane Detection +4

CLIP2: Contrastive Language-Image-Point Pretraining From Real-World Point Cloud Data

no code implementations CVPR 2023 Yihan Zeng, Chenhan Jiang, Jiageng Mao, Jianhua Han, Chaoqiang Ye, Qingqiu Huang, Dit-yan Yeung, Zhen Yang, Xiaodan Liang, Hang Xu

Contrastive Language-Image Pre-training, benefiting from large-scale unlabeled text-image pairs, has demonstrated great performance in open-world vision understanding tasks.

NLIP: Noise-robust Language-Image Pre-training

no code implementations14 Dec 2022 Runhui Huang, Yanxin Long, Jianhua Han, Hang Xu, Xiwen Liang, Chunjing Xu, Xiaodan Liang

Large-scale cross-modal pre-training paradigms have recently shown ubiquitous success on a wide range of downstream tasks, e. g., zero-shot classification, retrieval and image captioning.

Image Captioning Memorization +3

P$^3$OVD: Fine-grained Visual-Text Prompt-Driven Self-Training for Open-Vocabulary Object Detection

no code implementations2 Nov 2022 Yanxin Long, Jianhua Han, Runhui Huang, Xu Hang, Yi Zhu, Chunjing Xu, Xiaodan Liang

Inspired by the success of visual-language methods (VLMs) in zero-shot classification, recent works attempt to extend this line of work into object detection by leveraging the localization ability of pre-trained VLMs and generating pseudo labels for unseen classes in a self-training manner.

object-detection Open Vocabulary Object Detection +3

DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection

no code implementations20 Sep 2022 Lewei Yao, Jianhua Han, Youpeng Wen, Xiaodan Liang, Dan Xu, Wei zhang, Zhenguo Li, Chunjing Xu, Hang Xu

We further design a concept dictionary~(with descriptions) from various online sources and detection datasets to provide prior knowledge for each concept.

object-detection Open World Object Detection

Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving

no code implementations19 Sep 2022 Xiwen Liang, Yangxin Wu, Jianhua Han, Hang Xu, Chunjing Xu, Xiaodan Liang

Aiming towards a holistic understanding of multiple downstream tasks simultaneously, there is a need for extracting features with better transferability.

Autonomous Driving Multi-Task Learning +4

Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding

no code implementations18 Jul 2022 Quande Liu, Youpeng Wen, Jianhua Han, Chunjing Xu, Hang Xu, Xiaodan Liang

To bridge the gap between supervised semantic segmentation and real-world applications that acquires one model to recognize arbitrary new concepts, recent zero-shot segmentation attracts a lot of attention by exploring the relationships between unseen and seen object categories, yet requiring large amounts of densely-annotated data with diverse base classes.

Online Clustering Semantic Segmentation +1

Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing

no code implementations26 May 2022 Zhili Liu, Jianhua Han, Lanqing Hong, Hang Xu, Kai Chen, Chunjing Xu, Zhenguo Li

On the other hand, for existing SSL methods, it is burdensome and infeasible to use different downstream-task-customized datasets in pre-training for different tasks.

Self-Supervised Learning

Laneformer: Object-aware Row-Column Transformers for Lane Detection

no code implementations18 Mar 2022 Jianhua Han, Xiajun Deng, Xinyue Cai, Zhen Yang, Hang Xu, Chunjing Xu, Xiaodan Liang

We present Laneformer, a conceptually simple yet powerful transformer-based architecture tailored for lane detection that is a long-standing research topic for visual perception in autonomous driving.

Autonomous Driving Lane Detection

CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving

no code implementations15 Mar 2022 Kaican Li, Kai Chen, Haoyu Wang, Lanqing Hong, Chaoqiang Ye, Jianhua Han, Yukuai Chen, Wei zhang, Chunjing Xu, Dit-yan Yeung, Xiaodan Liang, Zhenguo Li, Hang Xu

One main reason that impedes the development of truly reliably self-driving systems is the lack of public datasets for evaluating the performance of object detectors on corner cases.

Autonomous Driving object-detection +1

SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving

no code implementations21 Jun 2021 Jianhua Han, Xiwen Liang, Hang Xu, Kai Chen, Lanqing Hong, Jiageng Mao, Chaoqiang Ye, Wei zhang, Zhenguo Li, Xiaodan Liang, Chunjing Xu

Experiments show that SODA10M can serve as a promising pre-training dataset for different self-supervised learning methods, which gives superior performance when fine-tuning with different downstream tasks (i. e., detection, semantic/instance segmentation) in autonomous driving domain.

Autonomous Driving Instance Segmentation +5

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