307 citations · 1.8k across the 219 of their papers we have counts for
12 papers · 1 filter
Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery
Mélisande Teng, Arthur Ouaknine, Etienne Laliberté +3
Information on trees at the individual level is crucial for monitoring forest ecosystems and planning forest management. Current monitoring methods involve ground measurements, req…
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery
Mélisande Teng, Arthur Ouaknine, Etienne Laliberté +3
The potential of tree planting as a natural climate solution is often undermined by inadequate monitoring of tree planting projects. Current monitoring methods involve measuring tr…
EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision
Diego Velazquez, Pau Rodriguez López, Sergio Alonso +6
This paper presents EarthView, a comprehensive dataset specifically designed for self-supervision on remote sensing data, intended to enhance deep learning applications on Earth mo…
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases
Cristian Meo, Akihiro Nakano, Mircea Lică +7
Unsupervised object-centric learning from videos is a promising approach towards learning compositional representations that can be applied to various downstream tasks, such as pre…
Zero-Shot Object-Centric Representation Learning
Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal +4
The goal of object-centric representation learning is to decompose visual scenes into a structured representation that isolates the entities. Recent successes have shown that objec…
VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text
Tianyu Zhang, Suyuchen Wang, Lu Li +6
We introduce Visual Caption Restoration (VCR), a novel vision-language task that challenges models to accurately restore partially obscured texts using pixel-level hints within ima…
Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks
Luca Scimeca, Alexander Rubinstein, Armand Mihai Nicolicioiu +2
Spurious correlations in the data, where multiple cues are predictive of the target labels, often lead to shortcut learning phenomena, where a model may rely on erroneous, easy-to-…
Cycle Consistency Driven Object Discovery
Aniket Didolkar, Anirudh Goyal, Yoshua Bengio
Developing deep learning models that effectively learn object-centric representations, akin to human cognition, remains a challenging task. Existing approaches facilitate object di…
Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior
Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal +2
The aim of object-centric vision is to construct an explicit representation of the objects in a scene. This representation is obtained via a set of interchangeable modules called \…
Leveraging the Third Dimension in Contrastive Learning
Sumukh Aithal, Anirudh Goyal, Alex Lamb +2
Self-Supervised Learning (SSL) methods operate on unlabeled data to learn robust representations useful for downstream tasks. Most SSL methods rely on augmentations obtained by tra…
Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya
Shimaa Baraka, Benjamin Akera, Bibek Aryal +7
Glacier mapping is key to ecological monitoring in the hkh region. Climate change poses a risk to individuals whose livelihoods depend on the health of glacier ecosystems. In this…
Visual Concept Reasoning Networks
Taesup Kim, Sungwoong Kim, Yoshua Bengio
A split-transform-merge strategy has been broadly used as an architectural constraint in convolutional neural networks for visual recognition tasks. It approximates sparsely connec…