414 citations · 1.1k across the 47 of their papers we have counts for
7 papers · 1 filter
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos
Jennifer J. Sun, Lili Karashchuk, Amil Dravid +9
Quantifying motion in 3D is important for studying the behavior of humans and other animals, but manual pose annotations are expensive and time-consuming to obtain. Self-supervised…
Visual Knowledge Tracing
Neehar Kondapaneni, Pietro Perona, Oisin Mac Aodha
Each year, thousands of people learn new visual categorization tasks -- radiologists learn to recognize tumors, birdwatchers learn to distinguish similar species, and crowd workers…
On Label Granularity and Object Localization
Elijah Cole, Kimberly Wilber, Grant Van Horn +6
Weakly supervised object localization (WSOL) aims to learn representations that encode object location using only image-level category labels. However, many objects can be labeled…
The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting
Justin Kay, Peter Kulits, Suzanne Stathatos +5
We present the Caltech Fish Counting Dataset (CFC), a large-scale dataset for detecting, tracking, and counting fish in sonar videos. We identify sonar videos as a rich source of d…
Near Perfect GAN Inversion
Qianli Feng, Viraj Shah, Raghudeep Gadde +2
To edit a real photo using Generative Adversarial Networks (GANs), we need a GAN inversion algorithm to identify the latent vector that perfectly reproduces it. Unfortunately, wher…
Towards Weakly-Supervised Text Spotting using a Multi-Task Transformer
Yair Kittenplon, Inbal Lavi, Sharon Fogel +3
Text spotting end-to-end methods have recently gained attention in the literature due to the benefits of jointly optimizing the text detection and recognition components. Existing…
Rayleigh EigenDirections (REDs): GAN latent space traversals for multidimensional features
Guha Balakrishnan, Raghudeep Gadde, Aleix Martinez +1
We present a method for finding paths in a deep generative model's latent space that can maximally vary one set of image features while holding others constant. Crucially, unlike p…