49 citations · 208 across the 23 of their papers we have counts for
20 papers · 1 filter
Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree
Hongsen Cao, Mona Jaber, Shanxin Yuan +1
Multi-modal fusion for 3D object detection assumes that cameras and LiDAR are broadly complementary. In practice, how much each modality is trusted at a given location is decided b…
Putting Registers to Work: Task Registers for Token Pruning in Vision Transformers
Hongsen Cao, Mona Jaber, Shanxin Yuan +1
Token-pruning policies are usually designed for a single recognition pipeline, but pretrained Vision Transformers are reused across tasks with different spatial demands. We ask whi…
Exploring Effective Mask Sampling Modeling for Neural Image Compression
Lin Liu, Mingming Zhao, Shanxin Yuan +5
Image compression aims to reduce the information redundancy in images. Most existing neural image compression methods rely on side information from hyperprior or context models to…
NeRFVS: Neural Radiance Fields for Free View Synthesis via Geometry Scaffolds
Chen Yang, Peihao Li, Zanwei Zhou +5
We present NeRFVS, a novel neural radiance fields (NeRF) based method to enable free navigation in a room. NeRF achieves impressive performance in rendering images for novel views…
Graph Neural Networks in Vision-Language Image Understanding: A Survey
Henry Senior, Gregory Slabaugh, Shanxin Yuan +1
2D image understanding is a complex problem within computer vision, but it holds the key to providing human-level scene comprehension. It goes further than identifying the objects…
Low-Light Video Enhancement with Synthetic Event Guidance
Lin Liu, Junfeng An, Jianzhuang Liu +6
Low-light video enhancement (LLVE) is an important yet challenging task with many applications such as photographing and autonomous driving. Unlike single image low-light enhanceme…
Disentangling 3D Attributes from a Single 2D Image: Human Pose, Shape and Garment
Xue Hu, Xinghui Li, Benjamin Busam +3
For visual manipulation tasks, we aim to represent image content with semantically meaningful features. However, learning implicit representations from images often lacks interpret…
TAPE: Task-Agnostic Prior Embedding for Image Restoration
Lin Liu, Lingxi Xie, Xiaopeng Zhang +5
Learning a generalized prior for natural image restoration is an important yet challenging task. Early methods mostly involved handcrafted priors including normalized sparsity, l_0…
SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers
Lin Liu, Shanxin Yuan, Jianzhuang Liu +3
We propose a novel zero-shot multi-frame image restoration method for removing unwanted obstruction elements (such as rains, snow, and moire patterns) that vary in successive frame…
Video Super-resolution with Temporal Group Attention
Takashi Isobe, Songjiang Li, Xu Jia +6
Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we pro…
Wavelet-Based Dual-Branch Network for Image Demoireing
Lin Liu, Jianzhuang Liu, Shanxin Yuan +4
When smartphone cameras are used to take photos of digital screens, usually moire patterns result, severely degrading photo quality. In this paper, we design a wavelet-based dual-b…
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Shanxin Yuan, Radu Timofte, Ales Leonardis +43
This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demo…
Image Demoireing with Learnable Bandpass Filters
Bolun Zheng, Shanxin Yuan, Gregory Slabaugh +1
Image demoireing is a multi-faceted image restoration task involving both texture and color restoration. In this paper, we propose a novel multiscale bandpass convolutional neural…
AIM 2019 Challenge on Image Demoireing: Dataset and Study
Shanxin Yuan, Radu Timofte, Gregory Slabaugh +1
This paper introduces a novel dataset, called LCDMoire, which was created for the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) wo…
RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images
Shanxin Yuan, Bjorn Stenger, Tae-Kyun Kim
This paper proposes a method for hand pose estimation from RGB images that uses both external large-scale depth image datasets and paired depth and RGB images as privileged informa…
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger +21
In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled?…
The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation
Shanxin Yuan, Qi Ye, Guillermo Garcia-Hernando +1
We present the 2017 Hands in the Million Challenge, a public competition designed for the evaluation of the task of 3D hand pose estimation. The goal of this challenge is to assess…
BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis
Shanxin Yuan, Qi Ye, Bjorn Stenger +2
In this paper we introduce a large-scale hand pose dataset, collected using a novel capture method. Existing datasets are either generated synthetically or captured using depth sen…
First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
Guillermo Garcia-Hernando, Shanxin Yuan, Seungryul Baek +1
In this work we study the use of 3D hand poses to recognize first-person dynamic hand actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences com…
Spatial Attention Deep Net with Partial PSO for Hierarchical Hybrid Hand Pose Estimation
Qi Ye, Shanxin Yuan, Tae-Kyun Kim
Discriminative methods often generate hand poses kinematically implausible, then generative methods are used to correct (or verify) these results in a hybrid method. Estimating 3D…