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Found 16 papers, 3 papers with code
End-to-End 3D Hand Pose Estimation from Stereo Cameras
This work proposes an end-to-end approach to estimate full 3D hand pose from stereo cameras.
Pose-based Body Language Recognition for Emotion and Psychiatric Symptom Interpretation
We then evaluate the framework on a proposed URMC dataset, which consists of conversations between a standardized patient and a behavioral health professional, along with expert annotations of body language, emotions, and potential psychiatric symptoms.
Dynamic Kernel Distillation for Efficient Pose Estimation in Videos
Existing video-based human pose estimation methods extensively apply large networks onto every frame in the video to localize body joints, which suffer high computational cost and hardly meet the low-latency requirement in realistic applications.
Ranked #4 on
2D Human Pose Estimation
on JHMDB (2D poses only)
Weakly Supervised Body Part Segmentation with Pose based Part Priors
The core idea is first converting the sparse weak labels such as keypoints to the initial estimate of body part masks, and then iteratively refine the part mask predictions.
Laplace Landmark Localization
Our method claims state-of-the-art on all of the 300W benchmarks and ranks second-to-best on the Annotated Facial Landmarks in the Wild (AFLW) dataset.
Ranked #5 on
Face Alignment
on AFLW-19
(NME_box (%, Full) metric)
3D Hand Shape and Pose Estimation from a Single RGB Image
This work addresses a novel and challenging problem of estimating the full 3D hand shape and pose from a single RGB image.
Skin Disease Classification versus Skin Lesion Characterization: Achieving Robust Diagnosis using Multi-label Deep Neural Networks
In contrast, for lesion-targeted classification, we can achieve a much higher mAP of 0. 70.
Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences
The attention mechanism is important for skeleton based action recognition because there exist spatio-temporal key stages while the joint predictions can be inaccurate.
Improving Pairwise Ranking for Multi-label Image Classification
Pairwise ranking, in particular, has been successful in multi-label image classification, achieving state-of-the-art results on various benchmarks.
Learning from Noisy Labels with Distillation
The ability of learning from noisy labels is very useful in many visual recognition tasks, as a vast amount of data with noisy labels are relatively easy to obtain.
Inferring Restaurant Styles by Mining Crowd Sourced Photos from User-Review Websites
The multi-label CNN is then used to compute the confidence scores of restaurant styles for all the images associated with a restaurant.
Mining Fashion Outfit Composition Using An End-to-End Deep Learning Approach on Set Data
The core of the proposed automatic composition system is to score fashion outfit candidates based on the appearances and meta-data.
TGIF: A New Dataset and Benchmark on Animated GIF Description
The motivation for this work is to develop a testbed for image sequence description systems, where the task is to generate natural language descriptions for animated GIFs or video clips.
Semantic Video Entity Linking Based on Visual Content and Metadata
In this paper, we propose to exploit video visual content to improve video entity linking.
Using User Generated Online Photos to Estimate and Monitor Air Pollution in Major Cities
With the rapid development of economy in China over the past decade, air pollution has become an increasingly serious problem in major cities and caused grave public health concerns in China.
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Asynchronous parallel implementations of stochastic gradient (SG) have been broadly used in solving deep neural network and received many successes in practice recently.
