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Found 18 papers, 8 papers with code
A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation
Multi-modality magnetic resonance imaging data with various sequences facilitate the early diagnosis, tumor segmentation, and disease staging in the management of nasopharyngeal carcinoma (NPC).
XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques
To address this, we introduce XRL-Bench, a unified standardized benchmark tailored for the evaluation and comparison of XRL methods, encompassing three main modules: standard RL environments, explainers based on state importance, and standard evaluators.
Sequential Model for Predicting Patient Adherence in Subcutaneous Immunotherapy for Allergic Rhinitis
Conclusion: We creatively apply sequential models in the long-term management of SCIT with promising accuracy in the prediction of SCIT nonadherence in Allergic Rhinitis (AR) patients.
PAD: Self-Supervised Pre-Training with Patchwise-Scale Adapter for Infrared Images
Self-supervised learning (SSL) for RGB images has achieved significant success, yet there is still limited research on SSL for infrared images, primarily due to three prominent challenges: 1) the lack of a suitable large-scale infrared pre-training dataset, 2) the distinctiveness of non-iconic infrared images rendering common pre-training tasks like masked image modeling (MIM) less effective, and 3) the scarcity of fine-grained textures making it particularly challenging to learn general image features.
Rethink Baseline of Integrated Gradients from the Perspective of Shapley Value
Thus, we propose a novel baseline construction method called Shapley Integrated Gradients (SIG) that searches for a set of baselines by proportional sampling to partly simulate the computation path of Shapley Value.
A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings
However, these methods lack a modelling mechanism to directly reflect user interests within the learned item representations.
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning
We first illustrate that the proposed value decomposition can consider the complicated interactions among agents and is feasible to learn in large-scale scenarios.
TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective
TCFimt constructs adversarial tasks in a seq2seq framework to alleviate selection and time-varying bias and designs a contrastive learning-based block to decouple a mixed treatment effect into separated main treatment effects and causal interactions which further improves estimation accuracy.
Plasticity Neural Network Based on Astrocytic effects at Critical Period, Synaptic Competition and Strength Rebalance by Current and Mnemonic Brain Plasticity and Synapse Formation
The relatively good and inferior gradient information stored in memory engram cells in synapse formation of retrograde circuit like the folds in brain [16].
Transcript to Video: Efficient Clip Sequencing from Texts
To meet the demands for non-experts, we present Transcript-to-Video -- a weakly-supervised framework that uses texts as input to automatically create video sequences from an extensive collection of shots.
MovieNet: A Holistic Dataset for Movie Understanding
We believe that such a holistic dataset would promote the researches on story-based long video understanding and beyond.
A Local-to-Global Approach to Multi-modal Movie Scene Segmentation
Scene, as the crucial unit of storytelling in movies, contains complex activities of actors and their interactions in a physical environment.
A Graph-Based Framework to Bridge Movies and Synopses
On top of this dataset, we develop a framework to perform matching between movie segments and synopsis paragraphs.
MMDetection: Open MMLab Detection Toolbox and Benchmark
In this paper, we introduce the various features of this toolbox.
Hybrid Task Cascade for Instance Segmentation
In exploring a more effective approach, we find that the key to a successful instance segmentation cascade is to fully leverage the reciprocal relationship between detection and segmentation.
Ranked #32 on
Object Detection
on COCO-O
Find and Focus: Retrieve and Localize Video Events with Natural Language Queries
The thriving of video sharing services brings new challenges to video retrieval, e. g. the rapid growth in video duration and content diversity.
From Trailers to Storylines: An Efficient Way to Learn from Movies
Experiments on this dataset showed that the proposed method can substantially reduce the training time while obtaining highly effective features and coherent temporal structures.
Unifying Identification and Context Learning for Person Recognition
In this work, we aim to move beyond such limitations and propose a new framework to leverage context for person recognition.
