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Found 17 papers, 6 papers with code
MBDF-Net: Multi-Branch Deep Fusion Network for 3D Object Detection
Fusing the two kinds of data usually helps to improve the detection results.
Probabilistic Human Motion Prediction via A Bayesian Neural Network
The experimental results show that our approach makes the interaction more efficient and safer.
HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration
Our experimental results show that the proposed method is able to perform high-quality restoration for unconstrained underwater images without any supervision.
Word-Free Spoken Language Understanding for Mandarin-Chinese
Spoken dialogue systems such as Siri and Alexa provide great convenience to people's everyday life.
Adaptive Feature Alignment for Adversarial Training
Based on this observation, we propose the adaptive feature alignment (AFA) to generate features of arbitrary attacking strengths.
SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance
Thus, we propose a novel unsupervised FIQA method that incorporates Similarity Distribution Distance for Face Image Quality Assessment (SDD-FIQA).
Camera-Space Hand Mesh Recovery via Semantic Aggregation and Adaptive 2D-1D Registration
In the root-relative mesh recovery task, we exploit semantic relations among joints to generate a 3D mesh from the extracted 2D cues.
WebSRC: A Dataset for Web-Based Structural Reading Comprehension
This task requires a system not only to understand the semantics of texts but also the structure of the web page.
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation
Tests on AFLW2000-3D and BIWI show that our method runs at real-time and outperforms state of the art (SotA) face pose estimators.
Ranked #2 on
Head Pose Estimation
on AFLW2000
S3ML: A Secure Serving System for Machine Learning Inference
We present S3ML, a secure serving system for machine learning inference in this paper.
A Boundary Based Out-of-Distribution Classifier for Generalized Zero-Shot Learning
Using a gating mechanism that discriminates the unseen samples from the seen samples can decompose the GZSL problem to a conventional Zero-Shot Learning (ZSL) problem and a supervised classification problem.
Reveal of Domain Effect: How Visual Restoration Contributes to Object Detection in Aquatic Scenes
According to our analysis, five key discoveries are reported: 1) Domain quality has an ignorable effect on within-domain convolutional representation and detection accuracy; 2) low-quality domain leads to higher generalization ability in cross-domain detection; 3) low-quality domain can hardly be well learned in a domain-mixed learning process; 4) degrading recall efficiency, restoration cannot improve within-domain detection accuracy; 5) visual restoration is beneficial to detection in the wild by reducing the domain shift between training data and real-world scenes.
Rethinking Temporal Object Detection from Robotic Perspectives
From a robotic perspective, the importance of recall continuity and localization stability is equal to that of accuracy, but the AP is insufficient to reflect detectors' performance across time.
Proportionally Fair Clustering
We extend the fair machine learning literature by considering the problem of proportional centroid clustering in a metric context.
Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos
As for temporal detection in videos, temporal refinement networks (TRNet) and temporal dual refinement networks (TDRNet) are developed by propagating the refinement information across time.
Temporally Identity-Aware SSD with Attentional LSTM
Moreover, we develop a creative temporal analysis unit, namely, attentional ConvLSTM (AC-LSTM), in which a temporal attention mechanism is specially tailored for background suppression and scale suppression while a ConvLSTM integrates attention-aware features across time.
Towards Real-Time Advancement of Underwater Visual Quality with GAN
More specifically, an underwater index is investigated to describe underwater properties, and a loss function based on the underwater index is designed to train the critic branch for underwater noise suppression.