206 citations · 486 across the 43 of their papers we have counts for
14 papers · 1 filter
ConQueR: Query Contrast Voxel-DETR for 3D Object Detection
Benjin Zhu, Zhe Wang, Shaoshuai Shi +3
Although DETR-based 3D detectors can simplify the detection pipeline and achieve direct sparse predictions, their performance still lags behind dense detectors with post-processing…
3D-TOGO: Towards Text-Guided Cross-Category 3D Object Generation
Zutao Jiang, Guansong Lu, Xiaodan Liang +4
Text-guided 3D object generation aims to generate 3D objects described by user-defined captions, which paves a flexible way to visualize what we imagined. Although some works have…
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection
Lewei Yao, Jianhua Han, Youpeng Wen +6
Open-world object detection, as a more general and challenging goal, aims to recognize and localize objects described by arbitrary category names. The recent work GLIP formulates t…
Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving
Xiwen Liang, Yangxin Wu, Jianhua Han +3
Aiming towards a holistic understanding of multiple downstream tasks simultaneously, there is a need for extracting features with better transferability. Though many latest self-su…
Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding
Quande Liu, Youpeng Wen, Jianhua Han +3
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 at…
Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing
Zhili Liu, Jianhua Han, Lanqing Hong +4
Self-supervised learning (SSL), especially contrastive methods, has raised attraction recently as it learns effective transferable representations without semantic annotations. A c…
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
Binbin Yang, Xinchi Deng, Han Shi +6
Continual learning is a challenging real-world problem for constructing a mature AI system when data are provided in a streaming fashion. Despite recent progress in continual class…
MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection
Xuesong Chen, Shaoshuai Shi, Benjin Zhu +3
Accurate and reliable 3D detection is vital for many applications including autonomous driving vehicles and service robots. In this paper, we present a flexible and high-performanc…
ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and Generation
Jianan Wang, Guansong Lu, Hang Xu +3
Existing text-guided image manipulation methods aim to modify the appearance of the image or to edit a few objects in a virtual or simple scenario, which is far from practical appl…
Point2Seq: Detecting 3D Objects as Sequences
Yujing Xue, Jiageng Mao, Minzhe Niu +5
We present a simple and effective framework, named Point2Seq, for 3D object detection from point clouds. In contrast to previous methods that normally {predict attributes of 3D obj…
Laneformer: Object-aware Row-Column Transformers for Lane Detection
Jianhua Han, Xiajun Deng, Xinyue Cai +4
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…
Visual-Language Navigation Pretraining via Prompt-based Environmental Self-exploration
Xiwen Liang, Fengda Zhu, Lingling Li +2
Vision-language navigation (VLN) is a challenging task due to its large searching space in the environment. To address this problem, previous works have proposed some methods of fi…
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving
Kaican Li, Kai Chen, Haoyu Wang +10
Contemporary deep-learning object detection methods for autonomous driving usually assume prefixed categories of common traffic participants, such as pedestrians and cars. Most exi…
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark
Jiaxi Gu, Xiaojun Meng, Guansong Lu +9
Vision-Language Pre-training (VLP) models have shown remarkable performance on various downstream tasks. Their success heavily relies on the scale of pre-trained cross-modal datase…