8 citations · 23 across the 10 of their papers we have counts for
10 papers
LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs
Zezhou Cheng, Carlos Esteves, Varun Jampani +3
A critical obstacle preventing NeRF models from being deployed broadly in the wild is their reliance on accurate camera poses. Consequently, there is growing interest in extending…
Accidental Turntables: Learning 3D Pose by Watching Objects Turn
Zezhou Cheng, Matheus Gadelha, Subhransu Maji
We propose a technique for learning single-view 3D object pose estimation models by utilizing a new source of data -- in-the-wild videos where objects turn. Such videos are prevale…
Cross-Modal 3D Shape Generation and Manipulation
Zezhou Cheng, Menglei Chai, Jian Ren +5
Creating and editing the shape and color of 3D objects require tremendous human effort and expertise. Compared to direct manipulation in 3D interfaces, 2D interactions such as sket…
Improving Few-Shot Part Segmentation using Coarse Supervision
Oindrila Saha, Zezhou Cheng, Subhransu Maji
A significant bottleneck in training deep networks for part segmentation is the cost of obtaining detailed annotations. We propose a framework to exploit coarse labels such as figu…
GANORCON: Are Generative Models Useful for Few-shot Segmentation?
Oindrila Saha, Zezhou Cheng, Subhransu Maji
Advances in generative modeling based on GANs has motivated the community to find their use beyond image generation and editing tasks. In particular, several recent works have show…
A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification
Jong-Chyi Su, Zezhou Cheng, Subhransu Maji
We evaluate the effectiveness of semi-supervised learning (SSL) on a realistic benchmark where data exhibits considerable class imbalance and contains images from novel classes. Ou…
On Equivariant and Invariant Learning of Object Landmark Representations
Zezhou Cheng, Jong-Chyi Su, Subhransu Maji
Given a collection of images, humans are able to discover landmarks by modeling the shared geometric structure across instances. This idea of geometric equivariance has been widely…
Detecting and Tracking Communal Bird Roosts in Weather Radar Data
Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani +4
The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers a…
A Bayesian Perspective on the Deep Image Prior
Zezhou Cheng, Matheus Gadelha, Subhransu Maji +1
The deep image prior was recently introduced as a prior for natural images. It represents images as the output of a convolutional network with random inputs. For "inference", gradi…
Deep Colorization
Zezhou Cheng, Qingxiong Yang, Bin Sheng
This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a very difficult problem and normally requires manual adjustme…