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Found 11 papers, 2 papers with code
Can Text-to-image Model Assist Multi-modal Learning for Visual Recognition with Visual Modality Missing?
Specifically, we propose a simple but effective multi-modal learning framework GTI-MM to enhance the data efficiency and model robustness against missing visual modality by imputing the missing data with generative transformers.
Context Unlocks Emotions: Text-based Emotion Classification Dataset Auditing with Large Language Models
In this work, we propose a formal definition of textual context to motivate a prompting strategy to enhance such contextual information.
Does Video Summarization Require Videos? Quantifying the Effectiveness of Language in Video Summarization
Video summarization remains a huge challenge in computer vision due to the size of the input videos to be summarized.
Robot Goes Fishing: Rapid, High-Resolution Biological Hotspot Mapping in Coral Reefs with Vision-Guided Autonomous Underwater Vehicles
Coral reefs are fast-changing and complex ecosystems that are crucial to monitor and study.
Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy
The bladder contour quality was primarily affected by using IV contrast.
Camera-Based Piano Sheet Music Identification
This paper presents a method for large-scale retrieval of piano sheet music images.
Robotic Grasping through Combined image-Based Grasp Proposal and 3D Reconstruction
We present a novel approach to robotic grasp planning using both a learned grasp proposal network and a learned 3D shape reconstruction network.
Robotics
QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error
We implement the objective with an adversarial Q-learning method in which Q and Qx are the action-value functions for extrinsic and secondary rewards, respectively.
Reward Prediction Error as an Exploration Objective in Deep RL
We then propose a deep reinforcement learning method, QXplore, which exploits the temporal difference error of a Q-function to solve hard exploration tasks in high-dimensional MDPs.
Demo2Vec: Reasoning Object Affordances From Online Videos
Watching expert demonstrations is an important way for humans and robots to reason about affordances of unseen objects.
Ranked #2 on
Video-to-image Affordance Grounding
on OPRA (28x28)
Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging
We propose predicting patient response to PRT from baseline task-based fMRI by the novel application of a random forest and tree bagging strategy.
