113 citations · 207 across the 21 of their papers we have counts for
22 papers
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…
Nuisance-Label Supervision: Robustness Improvement by Free Labels
Xinyue Wei, Weichao Qiu, Yi Zhang +2
In this paper, we present a Nuisance-label Supervision (NLS) module, which can make models more robust to nuisance factor variations. Nuisance factors are those irrelevant to a tas…
Simulated Adversarial Testing of Face Recognition Models
Nataniel Ruiz, Adam Kortylewski, Weichao Qiu +4
Most machine learning models are validated and tested on fixed datasets. This can give an incomplete picture of the capabilities and weaknesses of the model. Such weaknesses can be…
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation
Jiteng Mu, Weichao Qiu, Adam Kortylewski +3
Recent work has made significant progress on using implicit functions, as a continuous representation for 3D rigid object shape reconstruction. However, much less effort has been d…
Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles
Qing Liu, Adam Kortylewski, Zhishuai Zhang +7
Part segmentations provide a rich and detailed part-level description of objects. However, their annotation requires an enormous amount of work, which makes it difficult to apply s…
Nothing But Geometric Constraints: A Model-Free Method for Articulated Object Pose Estimation
Qihao Liu, Weichao Qiu, Weiyao Wang +2
We propose an unsupervised vision-based system to estimate the joint configurations of the robot arm from a sequence of RGB or RGB-D images without knowing the model a priori, and…
AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild
Zhe Zhang, Chunyu Wang, Weichao Qiu +2
Occlusion is probably the biggest challenge for human pose estimation in the wild. Typical solutions often rely on intrusive sensors such as IMUs to detect occluded joints. To make…
Identity Preserve Transform: Understand What Activity Classification Models Have Learnt
Jialing Lyu, Weichao Qiu, Xinyue Wei +3
Activity classification has observed great success recently. The performance on small dataset is almost saturated and people are moving towards larger datasets. What leads to the p…
Car Pose in Context: Accurate Pose Estimation with Ground Plane Constraints
Pengfei Li, Weichao Qiu, Michael Peven +2
Scene context is a powerful constraint on the geometry of objects within the scene in cases, such as surveillance, where the camera geometry is unknown and image quality may be poo…
RSA: Randomized Simulation as Augmentation for Robust Human Action Recognition
Yi Zhang, Xinyue Wei, Weichao Qiu +3
Despite the rapid growth in datasets for video activity, stable robust activity recognition with neural networks remains challenging. This is in large part due to the explosion of…
Learning from Synthetic Animals
Jiteng Mu, Weichao Qiu, Gregory Hager +1
Despite great success in human parsing, progress for parsing other deformable articulated objects, like animals, is still limited by the lack of labeled data. In this paper, we use…
DASZL: Dynamic Action Signatures for Zero-shot Learning
Tae Soo Kim, Jonathan D. Jones, Michael Peven +6
There are many realistic applications of activity recognition where the set of potential activity descriptions is combinatorially large. This makes end-to-end supervised training o…
Identifying Model Weakness with Adversarial Examiner
Michelle Shu, Chenxi Liu, Weichao Qiu +1
Machine learning models are usually evaluated according to the average case performance on the test set. However, this is not always ideal, because in some sensitive domains (e.g.…
Patch-based 3D Human Pose Refinement
Qingfu Wan, Weichao Qiu, Alan L. Yuille
State-of-the-art 3D human pose estimation approaches typically estimate pose from the entire RGB image in a single forward run. In this paper, we develop a post-processing step to…
CRAVES: Controlling Robotic Arm with a Vision-based Economic System
Yiming Zuo, Weichao Qiu, Lingxi Xie +3
Training a robotic arm to accomplish real-world tasks has been attracting increasing attention in both academia and industry. This work discusses the role of computer vision algori…
Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data
Yutong Bai, Qing Liu, Lingxi Xie +3
Detecting semantic parts of an object is a challenging task in computer vision, particularly because it is hard to construct large annotated datasets due to the difficulty of annot…
SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data
Qi Chen, Weichao Qiu, Yi Zhang +2
State-of-the-art techniques of artificial intelligence, in particular deep learning, are mostly data-driven. However, collecting and manually labeling a large scale dataset is both…
Adversarial Attacks Beyond the Image Space
Xiaohui Zeng, Chenxi Liu, Yu-Siang Wang +5
Generating adversarial examples is an intriguing problem and an important way of understanding the working mechanism of deep neural networks. Most existing approaches generated per…
ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond
Siyuan Qiao, Wei Shen, Weichao Qiu +2
Motivated by product detection in supermarkets, this paper studies the problem of object proposal generation in supermarket images and other natural images. We argue that estimatio…
UnrealStereo: Controlling Hazardous Factors to Analyze Stereo Vision
Yi Zhang, Weichao Qiu, Qi Chen +2
A reliable stereo algorithm is critical for many robotics applications. But textureless and specular regions can easily cause failure by making feature matching difficult. Understa…
UnrealCV: Connecting Computer Vision to Unreal Engine
Weichao Qiu, Alan Yuille
Computer graphics can not only generate synthetic images and ground truth but it also offers the possibility of constructing virtual worlds in which: (i) an agent can perceive, nav…
Ground-truth dataset and baseline evaluations for image base-detail separation algorithms
Xuan Dong, Boyan Bonev, Weixin Li +3
Base-detail separation is a fundamental computer vision problem consisting of modeling a smooth base layer with the coarse structures, and a detail layer containing the texture-lik…