activity
20152023
most citedInstant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

26 citations · 47 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2023

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…

cs.CV20231 cited

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…

cs.CV2021

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…

cs.CV20212 cited

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…

cs.CV202126 cited

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…

cs.CV2021

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…