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Found 32 papers, 8 papers with code
The Sogou-TIIC Speech Translation System for IWSLT 2018
Our final average result on speech translation is 31. 02 BLEU.
Guiding Text-to-Image Diffusion Model Towards Grounded Generation
The goal of this paper is to augment a pre-trained text-to-image diffusion model with the ability of open-vocabulary objects grounding, i. e., simultaneously generating images and segmentation masks for the corresponding visual entities described in the text prompt.
Integrating features from lymph node stations for metastatic lymph node detection
The branch targets to solve a closely related task on the LN station level, i. e., classifying whether an LN station contains metastatic LN or not, so as to learn representations for LN stations.
MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training
In this paper, we consider the problem of enhancing self-supervised visual-language pre-training (VLP) with medical-specific knowledge, by exploiting the paired image-text reports from the radiological daily practice.
Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization
And as a result, the dual-branch complementarity is effectively fused to promote a strong alliance.
Weakly-supervised Temporal Action Localization
Weakly Supervised Temporal Action Localization
FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation
However, in addition to previous explorations for improvement in federated averaging, our analysis shows that another critical bottleneck is the poorer optima of client models in more heterogeneous conditions.
Robust Collaborative 3D Object Detection in Presence of Pose Errors
Collaborative 3D object detection exploits information exchange among multiple agents to enhance accuracy of object detection in presence of sensor impairments such as occlusion.
Unrolled Graph Learning for Multi-Agent Collaboration
To fill this gap, we propose a distributed multi-agent learning model inspired by human collaboration, in which the agents can autonomously detect suitable collaborators and refer to collaborators' model for better performance.
Open-vocabulary Semantic Segmentation with Frozen Vision-Language Models
When trained at a sufficient scale, self-supervised learning has exhibited a notable ability to solve a wide range of visual or language understanding tasks.
Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation
Instead of learning a single prototype for each class, in this paper, we propose to use an adaptive number of prototypes to dynamically describe the different point patterns within a semantic class.
A Simple Plugin for Transforming Images to Arbitrary Scales
Existing models on super-resolution often specialized for one scale, fundamentally limiting their use in practical scenarios.
Low-Light Video Enhancement with Synthetic Event Guidance
Low-light video enhancement (LLVE) is an important yet challenging task with many applications such as photographing and autonomous driving.
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
Further, we apply the proposed framework to current SOTA multi-agent multi-modal forecasting systems as a plugin module, which enables the SOTA systems to 1) estimate the uncertainty in the multi-agent multi-modal trajectory forecasting task; 2) rank the multiple predictions and select the optimal one based on the estimated uncertainty.
Multi-level Fusion of Wav2vec 2.0 and BERT for Multimodal Emotion Recognition
The research and applications of multimodal emotion recognition have become increasingly popular recently.
Nextformer: A ConvNeXt Augmented Conformer For End-To-End Speech Recognition
To the best of our knowledge, the proposed Nextformer model achieves SOTA results on AISHELL-1(CER 4. 06%) and WenetSpeech(CER 7. 56%/11. 29%).
Ranked #1 on
Speech Recognition
on AISHELL-1
(CER metric)
K-Space Transformer for Undersampled MRI Reconstruction
This paper considers the problem of undersampled MRI reconstruction.
Contrastive Learning with Boosted Memorization
Different from previous works, we explore this direction from an alternative perspective, i. e., the data perspective, and propose a novel Boosted Contrastive Learning (BCL) method.
Self-Supervised Masking for Unsupervised Anomaly Detection and Localization
To extend the reconstruction-based anomaly detection architecture to the localized anomalies, we propose a self-supervised learning approach through random masking and then restoring, named Self-Supervised Masking (SSM) for unsupervised anomaly detection and localization.
Handwritten Mathematical Expression Recognition via Attention Aggregation based Bi-directional Mutual Learning
Handwritten mathematical expression recognition aims to automatically generate LaTeX sequences from given images.
Self-supervised Tumor Segmentation through Layer Decomposition
In this paper, we target self-supervised representation learning for zero-shot tumor segmentation.
Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction
The core of MST-GNN is a multiscale spatio-temporal graph that explicitly models the relations in motions at various spatial and temporal scales.
Cooperative Learning for Noisy Supervision
Learning with noisy labels has gained the enormous interest in the robust deep learning area.
MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets
A novel Multi-teacher Single-student Knowledge Distillation (MS-KD) framework is proposed, where the teacher models are pre-trained single-organ segmentation networks, and the student model is a multi-organ segmentation network.
A Fourier-based Framework for Domain Generalization
Modern deep neural networks suffer from performance degradation when evaluated on testing data under different distributions from training data.
H2O: A Benchmark for Visual Human-human Object Handover Analysis
Besides, we also report the hand and object pose errors with existing baselines and show that the dataset can serve as the video demonstrations for robot imitation learning on the handover task.
Collaborative Label Correction via Entropy Thresholding
Deep neural networks (DNNs) have the capacity to fit extremely noisy labels nonetheless they tend to learn data with clean labels first and then memorize those with noisy labels.
Divide and Conquer for Single-Frame Temporal Action Localization
Single-frame temporal action localization (STAL) aims to localize actions in untrimmed videos with only one timestamp annotation for each action instance.
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine Translation
Previous research for adapting a general neural machine translation (NMT) model into a specific domain usually neglects the diversity in translation within the same domain, which is a core problem for domain adaptation in real-world scenarios.
Point-Level Temporal Action Localization: Bridging Fully-supervised Proposals to Weakly-supervised Losses
Point-Level temporal action localization (PTAL) aims to localize actions in untrimmed videos with only one timestamp annotation for each action instance.
Ranked #2 on
Weakly Supervised Action Localization
on BEOID
Privileged Knowledge Distillation for Online Action Detection
Knowledge distillation is employed to transfer the privileged information from the offline teacher to the online student.
Ranked #5 on
Online Action Detection
on TVSeries
SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation
We demonstrate the effectiveness of our methods on two downstream tasks: i) Brain tumor segmentation, ii) Pancreas tumor segmentation.
Defending Adversarial Attacks by Correcting logits
Generating and eliminating adversarial examples has been an intriguing topic in the field of deep learning.
