26 citations · 62 across the 16 of their papers we have counts for
17 papers
Improved Neural Radiance Fields Using Pseudo-depth and Fusion
Jingliang Li, Qiang Zhou, Chaohui Yu +4
Since the advent of Neural Radiance Fields, novel view synthesis has received tremendous attention. The existing approach for the generalization of radiance field reconstruction pr…
Points-to-3D: Bridging the Gap between Sparse Points and Shape-Controllable Text-to-3D Generation
Chaohui Yu, Qiang Zhou, Jingliang Li +3
Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on score d…
DPF: Learning Dense Prediction Fields with Weak Supervision
Xiaoxue Chen, Yuhang Zheng, Yupeng Zheng +4
Nowadays, many visual scene understanding problems are addressed by dense prediction networks. But pixel-wise dense annotations are very expensive (e.g., for scene parsing) or impo…
D2Q-DETR: Decoupling and Dynamic Queries for Oriented Object Detection with Transformers
Qiang Zhou, Chaohui Yu, Zhibin Wang +1
Despite the promising results, existing oriented object detection methods usually involve heuristically designed rules, e.g., RRoI generation, rotated NMS. In this paper, we propos…
Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation
Chaohui Yu, Qiang Zhou, Jingliang Li +3
Modern incremental learning for semantic segmentation methods usually learn new categories based on dense annotations. Although achieve promising results, pixel-by-pixel labeling i…
MimCo: Masked Image Modeling Pre-training with Contrastive Teacher
Qiang Zhou, Chaohui Yu, Hao Luo +2
Recent masked image modeling (MIM) has received much attention in self-supervised learning (SSL), which requires the target model to recover the masked part of the input image. Alt…
Point RCNN: An Angle-Free Framework for Rotated Object Detection
Qiang Zhou, Chaohui Yu, Zhibin Wang +1
Rotated object detection in aerial images is still challenging due to arbitrary orientations, large scale and aspect ratio variations, and extreme density of objects. Existing stat…
Point-Teaching: Weakly Semi-Supervised Object Detection with Point Annotations
Yongtao Ge, Qiang Zhou, Xinlong Wang +3
Point annotations are considerably more time-efficient than bounding box annotations. However, how to use cheap point annotations to boost the performance of semi-supervised object…
LUAI Challenge 2021 on Learning to Understand Aerial Images
Gui-Song Xia, Jian Ding, Ming Qian +33
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…
Delving Deep into the Generalization of Vision Transformers under Distribution Shifts
Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang +6
Vision Transformers (ViTs) have achieved impressive performance on various vision tasks, yet their generalization under distribution shifts (DS) is rarely understood. In this work,…
Human De-occlusion: Invisible Perception and Recovery for Humans
Qiang Zhou, Shiyin Wang, Yitong Wang +2
In this paper, we tackle the problem of human de-occlusion which reasons about occluded segmentation masks and invisible appearance content of humans. In particular, a two-stage fr…
Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework
Qiang Zhou, Chaohui Yu, Zhibin Wang +2
Supervised learning based object detection frameworks demand plenty of laborious manual annotations, which may not be practical in real applications. Semi-supervised object detecti…
Object Detection Made Simpler by Eliminating Heuristic NMS
Qiang Zhou, Chaohui Yu, Chunhua Shen +2
We show a simple NMS-free, end-to-end object detection framework, of which the network is a minimal modification to a one-stage object detector such as the FCOS detection model [Ti…
A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition
Jingjing Cao, Fukang Guo, Xin Lai +2
With the propagation of sensor devices applied in smart home, activity recognition has ignited huge interest and most existing works assume that there is only one habitant. While i…
Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation
Qiang Zhou, Zilong Huang, Lichao Huang +5
Video object segmentation (VOS) aims at pixel-level object tracking given only the annotations in the first frame. Due to the large visual variations of objects in video and the la…
STN-Homography: estimate homography parameters directly
Qiang Zhou, Xin Li
In this paper, we introduce the STN-Homography model to directly estimate the homography matrix between image pair. Different most CNN-based homography estimation methods which use…
Probabilistic Belief Embedding for Knowledge Base Completion
Miao Fan, Qiang Zhou, Andrew Abel +2
This paper contributes a novel embedding model which measures the probability of each belief in a large-scale knowledge repository via simultaneously learn…