We propose InCA, a lightweight method for transfer learning that
cross-a...
Nonparametric based methods have recently shown promising results in
rec...
Adapting pre-trained models with broad capabilities has become standard
...
Reference-guided image inpainting restores image pixels by leveraging th...
Traditionally, distillation has been used to train a student model to em...
Fine-tuning from a collection of models pre-trained on different domains...
We present a plug-in replacement for batch normalization (BN) called
exp...
Monocular depth prediction is a highly underdetermined problem and recen...
A system capturing the association between video frames and textual quer...
The nematode Caenorhabditis elegans (C. elegans) serves as an important ...
Leveraging synthetically rendered data offers great potential to improve...
Full 3D estimation of human pose from a single image remains a challengi...
Computer Vision applications often require a textual grounding module wi...
We introduce multigrid Predictive Filter Flow (mgPFF), a framework for
u...
Dynamic scenes that contain both object motion and egomotion are a chall...
We introduce a method to provide vectorial representations of visual
cla...
We propose a simple, interpretable framework for solving a wide range of...
Much recent work on visual recognition aims to scale up learning to mass...
To achieve parsimonious inference in per-pixel labeling tasks with a lim...
Automated facial expression analysis has a variety of applications in
hu...
Visual question answering (VQA) is of significant interest due to its
po...
We introduce a differentiable, end-to-end trainable framework for solvin...
Objects may appear at arbitrary scales in perspective images of a scene,...
Pooling second-order local feature statistics to form a high-dimensional...
Real-world applications could benefit from the ability to automatically
...
Micro-videos are six-second videos popular on social media networks with...
We study the problem of multi-target tracking and data association in vi...
Datasets for training object recognition systems are steadily increasing...