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20152023
most citedLarge-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

53 citations · 195 across the 17 of their papers we have counts for

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13 papers · 1 filter

cs.CV2023★ 2 cited

Cascade-DETR: Delving into High-Quality Universal Object Detection

Mingqiao Ye, Lei Ke, Siyuan Li +4

Object localization in general environments is a fundamental part of vision systems. While dominating on the COCO benchmark, recent Transformer-based detection methods are not comp…

cs.CV2023

OVTrack: Open-Vocabulary Multiple Object Tracking

Siyuan Li, Tobias Fischer, Lei Ke +3

The ability to recognize, localize and track dynamic objects in a scene is fundamental to many real-world applications, such as self-driving and robotic systems. Yet, traditional m…

cs.CV2023★ 9 cited

CLIP-ReID: Exploiting Vision-Language Model for Image Re-Identification without Concrete Text Labels

Siyuan Li, Li Sun, Qingli Li

Pre-trained vision-language models like CLIP have recently shown superior performances on various downstream tasks, including image classification and segmentation. However, in fin…

cs.CV2022

Tracking Every Thing in the Wild

Siyuan Li, Martin Danelljan, Henghui Ding +2

Current multi-category Multiple Object Tracking (MOT) metrics use class labels to group tracking results for per-class evaluation. Similarly, MOT methods typically only associate o…

cs.CV2022★ 2 cited

Style Transformer for Image Inversion and Editing

Xueqi Hu, Qiusheng Huang, Zhengyi Shi +4

Existing GAN inversion methods fail to provide latent codes for reliable reconstruction and flexible editing simultaneously. This paper presents a transformer-based image inversion…

cs.CV2020★ 3 cited

Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals

Siyuan Li, Semih Günel, Mirela Ostrek +3

Our goal is to capture the pose of neuroscience model organisms, without using any manual supervision, to be able to study how neural circuits orchestrate behaviour. Human pose est…

cs.CV2019

Single Image Deraining: A Comprehensive Benchmark Analysis

Siyuan Li, Iago Breno Araujo, Wenqi Ren +7

We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy i…

cs.CV2019★ 35 cited

PFLD: A Practical Facial Landmark Detector

Xiaojie Guo, Siyuan Li, Jinke Yu +5

Being accurate, efficient, and compact is essential to a facial landmark detector for practical use. To simultaneously consider the three concerns, this paper investigates a neat m…

cs.CV2018★ 14 cited

Fast Single Image Rain Removal via a Deep Decomposition-Composition Network

Siyuan LI, Wenqi Ren, Jiawan Zhang +2

Rain effect in images typically is annoying for many multimedia and computer vision tasks. For removing rain effect from a single image, deep leaning techniques have been attractin…

cs.CV2017★ 2 cited

Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs

Xinqing Guo, Zhang Chen, Siyuan Li +2

Human visual system relies on both binocular stereo cues and monocular focusness cues to gain effective 3D perception. In computer vision, the two problems are traditionally solved…

cs.CV2017★ 53 cited

Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

Li Yi, Lin Shao, Manolis Savva +47

We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…

cs.CV2017★ 11 cited

A Learning-based Framework for Hybrid Depth-from-Defocus and Stereo Matching

Zhang Chen, Xinqing Guo, Siyuan Li +2

Depth from defocus (DfD) and stereo matching are two most studied passive depth sensing schemes. The techniques are essentially complementary: DfD can robustly handle repetitive te…

cs.CV2015★ 1 cited

Visual Data Deblocking using Structural Layer Priors

Xiaojie Guo

The blocking artifact frequently appears in compressed real-world images or video sequences, especially coded at low bit rates, which is visually annoying and likely hurts the perf…