activity
20162022
most citedStreetStyle: Exploring world-wide clothing styles from millions of photos

41 citations · 55 across the 6 of their papers we have counts for

collaborators

18 papers

cs.CV20221 cited

Activation Regression for Continuous Domain Generalization with Applications to Crop Classification

Samar Khanna, Bram Wallace, Kavita Bala +1

Geographic variance in satellite imagery impacts the ability of machine learning models to generalise to new regions. In this paper, we model geographic generalisation in medium re…

cs.CV2021

AutoPhoto: Aesthetic Photo Capture using Reinforcement Learning

Hadi AlZayer, Hubert Lin, Kavita Bala

The process of capturing a well-composed photo is difficult and it takes years of experience to master. We propose a novel pipeline for an autonomous agent to automatically capture…

cs.CV2021

Field-Guide-Inspired Zero-Shot Learning

Utkarsh Mall, Bharath Hariharan, Kavita Bala

Modern recognition systems require large amounts of supervision to achieve accuracy. Adapting to new domains requires significant data from experts, which is onerous and can become…

cs.CV20219 cited

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting

Kai Zhang, Fujun Luan, Qianqian Wang +2

We present PhySG, an end-to-end inverse rendering pipeline that includes a fully differentiable renderer and can reconstruct geometry, materials, and illumination from scratch from…

cs.CV2021

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering

Jang Hyun Cho, Utkarsh Mall, Kavita Bala +1

We present a new framework for semantic segmentation without annotations via clustering. Off-the-shelf clustering methods are limited to curated, single-label, and object-centric i…

cs.CV2021

Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Rendering

Fujun Luan, Shuang Zhao, Kavita Bala +1

Reconstructing the shape and appearance of real-world objects using measured 2D images has been a long-standing problem in computer vision. In this paper, we introduce a new analys…