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Found 10 papers, 4 papers with code
InfiCoder-Eval: Systematically Evaluating the Question-Answering Capabilities of Code Large Language Models
Large Language Models for understanding and generating code (code LLMs) have witnessed tremendous progress in recent years.
Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling
Diffusion models excel at generating photo-realistic images but come with significant computational costs in both training and sampling.
Data Augmentation for Object Detection via Differentiable Neural Rendering
We propose a new offline data augmentation method for object detection, which semantically interpolates the training data with novel views.
LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking
To the best of our knowledge, this is the first paper to propose an online human pose tracking framework in a top-down fashion.
Ranked #3 on
Pose Tracking
on PoseTrack2017
A Top-down Approach to Articulated Human Pose Estimation and Tracking
Both the tasks of multi-person human pose estimation and pose tracking in videos are quite challenging.
Progressive Neural Networks for Image Classification
The inference structures and computational complexity of existing deep neural networks, once trained, are fixed and remain the same for all test images.
Dual Path Networks for Multi-Person Human Pose Estimation
The task of multi-person human pose estimation in natural scenes is quite challenging.
Knowledge Projection for Deep Neural Networks
In this paper, we will develop a new framework for training deep neural networks on datasets with limited labeled samples using cross-network knowledge projection which is able to improve the network performance while reducing the overall computational complexity significantly.
Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation
Human pose estimation using deep neural networks aims to map input images with large variations into multiple body keypoints which must satisfy a set of geometric constraints and inter-dependency imposed by the human body model.
Ranked #6 on
Pose Estimation
on Leeds Sports Poses
Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
In this paper, we develop a new approach of spatially supervised recurrent convolutional neural networks for visual object tracking.
