1. Automated analysis of bioacoustic recordings using machine learning (...
Estimating the geographical range of a species from sparse observations ...
We present Visual-Language Fields (VL-Fields), a neural implicit spatial...
We explore the problem of Incremental Generalized Category Discovery (IG...
Multimodal learning, which aims to understand and analyze information fr...
We introduce SAOR, a novel approach for estimating the 3D shape, texture...
We introduce ViewNeRF, a Neural Radiance Field-based viewpoint estimatio...
Understanding the 3D world without supervision is currently a major chal...
Precisely naming the action depicted in a video can be a challenging and...
Vision-language models such as CLIP are pretrained on large volumes of
i...
We present a new benchmark dataset, Sapsucker Woods 60 (SSW60), for adva...
Weakly supervised object localization (WSOL) aims to learn representatio...
Each year, thousands of people learn new visual categorization tasks –
r...
We explore semantic correspondence estimation through the lens of
unsupe...
We address the problem of capturing temporal information for video
class...
Fine-grained image analysis (FGIA) is a longstanding and fundamental pro...
We address the problem of learning self-supervised representations from
...
Predicting all applicable labels for a given image is known as multi-lab...
Recent self-supervised representation learning techniques have largely c...
Self-supervised monocular depth estimation networks are trained to predi...
Recent progress in self-supervised learning has resulted in models that ...
Supervised deep networks are among the best methods for finding
correspo...
We introduce an approach for updating older tree inventories with geogra...
Appearance information alone is often not sufficient to accurately
diffe...
Depth-sensing is important for both navigation and scene understanding.
...
How can we help a forgetful learner learn multiple concepts within a lim...
We address the problem of 3D human pose estimation from 2D input images ...
We study the problem of computer-assisted teaching with explanations.
Co...
In real-world applications of education and human teaching, an effective...
Low dimensional embeddings that capture the main variations of interest ...
Existing image classification datasets used in computer vision tend to h...
Learning based methods have shown very promising results for the task of...
To train good supervised and semi-supervised object classifiers, it is
c...
Compared to machines, humans are extremely good at classifying images in...