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Works62 from public data
- Visual Commonsense R-CNN299
A novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), is presented to serve as an improved visual region encoder for high-level tasks such as captioning and VQA, and observes consistent performance boosts across them.
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- Counterfactual Zero-Shot and Open-Set Visual Recognition249
A novel counterfactual framework for both Zero-Shot Learning (ZSL) and Open-Set Recognition (OSR), whose common challenge is generalizing to the unseen-classes by only training on the seen-classes is presented.
- Class Re-Activation Maps for Weakly-Supervised Semantic Segmentation235
An embarrassingly simple yet surprisingly effective method: Reactivating the converged CAM with BCE by using softmax crossentropy loss (SCE), dubbed ReCAM, which not only generates high-quality masks, but also supports plug-and-play in any CAM variant with little overhead.
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- Disco: Disentangled Control for Realistic Human Dance Generation187
Disco is introduced, which includes a novel model architecture with disentangled control to improve the compositionality of dance synthesis, and an effective human attribute pre-training for better generalizability to unseen humans.
- Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking177
This work proposes a novel Multi-modal Tensor Fusion Network (MTFN) to explicitly learn an accurate image-text similarity function with rank-based tensor fusion rather than seeking a common embedding space for each image- text instance.
- Causal Attention for Unbiased Visual Recognition174
A causal attention module (CaaM) that self-annotates the confounders in unsupervised fashion is proposed that can be stacked and integrated in conventional attention CNN and self-attention Vision Transformer, and in OOD settings, deep models with CaaM outperform those without it significantly.
- Conditional preferences and updating112
This paper axiomatizes updating rules for preferences that are not necessarily in the expected utility class: the traditional BayesRule, the Dempster–Shafer rule, and the generalized Bayes rule.
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- A Novel Pure Pursuit Algorithm for Autonomous Vehicles Based on Salp Swarm Algorithm and Velocity Controller88
A novel pure pursuit algorithm based on the optimized look-ahead distance named OLDPPA is proposed and experimental results show that the tracking accuracy of OL DPPA is better than other algorithms.
- An improved African vultures optimization algorithm based on tent chaotic mapping and time-varying mechanism81
A new metaheuristic algorithm, an improved African vultures optimization algorithm based on tent chaotic mapping and time-varying mechanism (TAVOA), is proposed, which shows good performance in real-world engineering design problems.
- Equivariant Similarity for Vision-Language Foundation Models74
This study proposes EqSim, a regularization loss that can be efficiently calculated from any two matched training pairs and easily pluggable into existing image-text retrieval fine-tuning and presents a new challenging benchmark EqBen, the first to focus on "visual-minimal change".
- A novel filter feature selection algorithm based on relief74
A novel feature selection algorithm, named Multidirectional Relief (MRelief), is proposed, which is significantly better than other algorithms including LPLIR, ReliefF, LLH-Relief, MultiSURF, MSLIR-NN, MRMR, MPMD and STIR in this study.
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- Impact of Social Participation Types on Depression in the Elderly in China: An Analysis Based on Counterfactual Causal Inference71
Through PSM analysis, different types of social participation have different effects on depression in the elderly, and it is necessary to provide differentiated social support environment for the elderly to maximize the positive effects of different typesof social participation.
- Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model60
The empirical results demonstrate that Diff-Mix achieves a better balance between faith-fulness and diversity, leading to a marked improvement in performance across diverse image classification scenarios, including few-shot, conventional, and long-tail classifications for domain-specific datasets.
- ClothFormer: Taming Video Virtual Try-on in All Module45
A novel video virtual try-on framework, ClothFormer, which successfully synthesizes realistic, harmonious, and spatio-temporal consistent results in complicated environment is proposed.
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- A Hybrid Improved Dragonfly Algorithm for Feature Selection41
A novel feature selection algorithm named hybrid improved dragonflies algorithm (HIDA) which combines the advantages of both mRMR and improved dragonfly algorithm (IDA) in order to generate promising candidate subset and achieve higher classification accuracy rate.
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- Equivariance and Invariance Inductive Bias for Learning from Insufficient Data26
State-of-the-art experimental results on real-world benchmarks (VIPriors, ImageNet100 and NICO) validate the great potential of equivariance and invariance in data-efficient learning.
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- Pricing of New Securities in an Incomplete Market: the Catch 22 of No‐Arbitrage Pricing18
This paper provides a simple proof that the introduction of the new security will typically change the prices of all the existing securities and clarifies the distinction between the two approaches to the valuation of a new security in an incomplete market.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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