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Found 14 papers, 8 papers with code
n-Reference Transfer Learning for Saliency Prediction
The proposed framework is gradient-based and model-agnostic.
Learning to Minimize the Remainder in Supervised Learning
To this end, we propose a new learning approach, namely gradient adjustment learning (GAL), to leverage the knowledge learned from the past training iterations to adjust vanilla gradients, such that the remainders are minimized and the approximations are improved.
Learning to Predict Trustworthiness with Steep Slope Loss
Secondly, due to the data complexity, it is challenging to differentiate the incorrect predictions from the correct ones on real-world large-scale datasets.
$n$-Reference Transfer Learning for Saliency Prediction
The proposed framework is gradient-based and model-agnostic.
Direction Concentration Learning: Enhancing Congruency in Machine Learning
We propose a Direction Concentration Learning (DCL) method to improve congruency in the learning process, where enhancing congruency influences the convergence path to be less circuitous.
Ranked #8 on
Image Classification
on Tiny ImageNet Classification
(using extra training data)
Embedding Symbolic Knowledge into Deep Networks
Interestingly, we observe a connection between the tractability of the propositional theory representation and the ease of embedding.
BEHAVIOR MODULE IN NEURAL NETWORKS
This property is particularly useful for user modeling (as for dialog agents) and recommendation tasks, as allows learning personalized representations of different user states.
Visual Social Relationship Recognition
Social relationships form the basis of social structure of humans.
Unsupervised Learning of View-invariant Action Representations
Different from previous works in video representation learning, our unsupervised learning task is to predict 3D motion in multiple target views using video representation from a source view.
Interact as You Intend: Intention-Driven Human-Object Interaction Detection
The recent advances in instance-level detection tasks lay strong foundation for genuine comprehension of the visual scenes.
Video Storytelling: Textual Summaries for Events
Video storytelling introduces new challenges, mainly due to the diversity of the story and the length and complexity of the video.
Emotional Attention: A Study of Image Sentiment and Visual Attention
In this paper, we present the first study to focus on the relation between emotional properties of an image and visual attention.
Dual-Glance Model for Deciphering Social Relationships
Since the beginning of early civilizations, social relationships derived from each individual fundamentally form the basis of social structure in our daily life.
Ranked #3 on
Visual Social Relationship Recognition
on PIPA
Group $K$-Means
We study how to learn multiple dictionaries from a dataset, and approximate any data point by the sum of the codewords each chosen from the corresponding dictionary.
