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Found 17 papers, 6 papers with code
Multi-granular Adversarial Attacks against Black-box Neural Ranking Models
However, limiting perturbations to a single level of granularity may reduce the flexibility of adversarial examples, thereby diminishing the potential threat of the attack.
Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off
We decompose the robust ranking error into two components, i. e., a natural ranking error for effectiveness evaluation and a boundary ranking error for assessing adversarial robustness.
Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method
The AREA task is meant to trick DR models into retrieving a target document that is outside the initial set of candidate documents retrieved by the DR model in response to a query.
On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective
Recently, we have witnessed generative retrieval increasingly gaining attention in the information retrieval (IR) field, which retrieves documents by directly generating their identifiers.
Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models
In this paper, we focus on a more general type of perturbation and introduce the topic-oriented adversarial ranking attack task against NRMs, which aims to find an imperceptible perturbation that can promote a target document in ranking for a group of queries with the same topic.
Gated Res2Net for Multivariate Time Series Analysis
Through the utilization of gated mechanism, the network can control the process of information sending hence can better capture and utilize the both the temporal information and the correlations between the feature maps.
Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains
Empirical evaluation shows that SML can detect cheating nodes at small cost to the predictive performance.
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identification
Meanwhile, we introduce "Semantic Fusion Branch" to filter out irrelevant noises by selectively fusing semantic region information sequentially.
DermGAN: Synthetic Generation of Clinical Skin Images with Pathology
Despite the recent success in applying supervised deep learning to medical imaging tasks, the problem of obtaining large and diverse expert-annotated datasets required for the development of high performant models remains particularly challenging.
WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing Detection
Quick detection of blade ice accretion is crucial for the maintenance of wind farms.
PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation
We further create a Truncation LINEMOD dataset to validate the robustness of our approach against truncation.
Ranked #2 on
6D Pose Estimation using RGB
on YCB-Video
(Mean AUC metric)
Pyramid Network with Online Hard Example Mining for Accurate Left Atrium Segmentation
Accurately segmenting left atrium in MR volume can benefit the ablation procedure of atrial fibrillation.
Thermal Infrared Colorization via Conditional Generative Adversarial Network
Transforming a thermal infrared image into a realistic RGB image is a challenging task.
VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling
Jointing visual-semantic embeddings (VSE) have become a research hotpot for the task of image annotation, which suffers from the issue of semantic gap, i. e., the gap between images' visual features (low-level) and labels' semantic features (high-level).
Nintendo Super Smash Bros. Melee: An "Untouchable" Agent
Nintendo's Super Smash Bros. Melee fighting game can be emulated on modern hardware allowing us to inspect internal memory states, such as character positions.
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications
Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.
Glasgow's Stereo Image Database of Garments
To provide insight into cloth perception and manipulation with an active binocular robotic vision system, we compiled a database of 80 stereo-pair colour images with corresponding horizontal and vertical disparity maps and mask annotations, for 3D garment point cloud rendering has been created and released.
