activity
20182023
most citedBEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

202 citations · 475 across the 16 of their papers we have counts for

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Showing cs.CVShow all

7 papers · 1 filter

cs.CV2022★ 1 cited

FlowNAS: Neural Architecture Search for Optical Flow Estimation

Zhiwei Lin, Tingting Liang, Taihong Xiao +3

Existing optical flow estimators usually employ the network architectures typically designed for image classification as the encoder to extract per-pixel features. However, due to…

cs.CV2022★ 202 cited

BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

Tingting Liang, Hongwei Xie, Kaicheng Yu +6

Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to lever…

cs.CV2021★ 177 cited

CBNet: A Composite Backbone Network Architecture for Object Detection

Tingting Liang, Xiaojie Chu, Yudong Liu +5

Modern top-performing object detectors depend heavily on backbone networks, whose advances bring consistent performance gains through exploring more effective network structures. I…

cs.CV2021★ 2 cited

RPATTACK: Refined Patch Attack on General Object Detectors

Hao Huang, Yongtao Wang, Zhaoyu Chen +3

Nowadays, general object detectors like YOLO and Faster R-CNN as well as their variants are widely exploited in many applications. Many works have revealed that these detectors are…

cs.CV2021★ 5 cited

OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection

Tingting Liang, Yongtao Wang, Zhi Tang +2

Recently, neural architecture search (NAS) has been exploited to design feature pyramid networks (FPNs) and achieved promising results for visual object detection. Encouraged by th…

cs.CV2020★ 3 cited

ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition

Zuoyu Yan, Xiaode Zhang, Liangcai Gao +2

Despite the recent advances in optical character recognition (OCR), mathematical expressions still face a great challenge to recognize due to their two-dimensional graphical layout…

cs.CV2018★ 14 cited

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

Qijie Zhao, Tao Sheng, Yongtao Wang +4

Feature pyramids are widely exploited by both the state-of-the-art one-stage object detectors (e.g., DSSD, RetinaNet, RefineDet) and the two-stage object detectors (e.g., Mask R-CN…