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- The Visual Object Tracking VOT2016 Challenge Results776
The Visual Object Tracking challenge VOT2016 goes beyond its predecessors by introducing a new semi-automatic ground truth bounding box annotation methodology and extending the evaluation system with the no-reset experiment.
- Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks608
The proposed approach preserves intermediate-to-high frequency details via an adversarial loss, and it offers enhanced synthesis performance via pixel-wise and perceptual losses for registered multi-contrast images and a cycle-consistency loss for unregistered images.
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- Visual saliency estimation by nonlinearly integrating features using region covariances417
This work proposes to use covariance matrices of simple image features (known as region covariance descriptors in the computer vision community) as meta-features for saliency estimation and demonstrates that the proposed approach outperforms the state-of-art models on various tasks including prediction of human eye fixations, salient object detection, and image-retargeting.
- Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures397
This survey classify the existing approaches based on how they conceptualize this problem, viz., models that cast description as either generation problem or as a retrieval problem over a visual or multimodal representational space.
- Structure-preserving image smoothing via region covariances219
This study proposes an alternative yet simple image smoothing approach which depends on covariance matrices of simple image features, aka the region covariances, and uses second order statistics as a patch descriptor to implicitly capture local structure and texture information.
- RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes198
This work introduces RecipeQA, a dataset for multimodal comprehension of cooking recipes, a set of comprehension and reasoning tasks that require joint understanding of images and text, capturing the temporal flow of events and making sense of procedural knowledge.
- Re-evaluating Automatic Metrics for Image Captioning195
This paper provides an in-depth evaluation of the existing image captioning metrics through a series of carefully designed experiments and explores the utilization of the recently proposed Word Mover’s Distance document metric for the purpose of image Captioning.
- mustGAN: multi-stream Generative Adversarial Networks for MR Image Synthesis185
Quantitative and radiological assessments on T1, T2, PD-weighted, and FLAIR images clearly demonstrate the superior performance of the proposed multi-stream approach that aggregates information across multiple source images via a mixture of multiple one- to-one streams and a joint many-to-one stream.
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- The State of the Art in HDR Deghosting: A Survey and Evaluation127
A taxonomy of deghosting algorithms is proposed which can be used to group existing and future algorithms into meaningful classes, and the results of a subjective experiment are shared which aims to evaluate various state‐of‐the‐art de ghosting algorithms.
- An Objective Deghosting Quality Metric for HDR Images113
An objective metric is proposed which aims to simplify the process of reconstructing high dynamic range images of a complex scene involving moving objects and dynamic backgrounds by taking a stack of input exposures and the deghosting result and producing a set of artifact maps for different types of artifacts.
- Inst-Inpaint: Instructing to Remove Objects with Diffusion Models93
This work presents a novel inpainting framework, Inst-Inpaint, that can remove objects from images based on the instructions given as text prompts and compares methods with different evaluation metrics that measure the quality and accuracy of the models and show significant quantitative and qualitative improvements.
- Disconnected Skeleton: Shape at Its Absolute Scale88
This work presents a new skeletal representation along with a matching framework to address the deformable shape recognition problem and replaces the local coordinate frame with a global Euclidean frame supported by additional mechanisms to handle articulations and local boundary deformations.
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- Deformable part-based tracking by coupled global and local correlation filters81
A deformable part-based correlation filter tracking approach which depends on coupled interactions between a global filter and several part filters, which gives significantly better results compared with the state-of-the-art trackers.
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- HyperE2VID: Improving Event-Based Video Reconstruction via Hypernetworks74
This study proposes HyperE2VID, a dynamic neural network architecture for event-based video reconstruction that uses hypernetworks to generate per-pixel adaptive filters guided by a context fusion module that combines information from event voxel grids and previously reconstructed intensity images.
- Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning68
This state-of-the-art report investigates the recent developments and applications of NNLG in its full extent from a multidimensional view, covering critical perspectives such as multimodality, multilinguality, controllability and learning strategies.
- The Thermal Infrared Visual Object Tracking VOT-TIR2016 Challenge Results66
A significant general improvement of results has been observed, which partly compensate for the more difficult sequences introduced into the dataset in VOT-TIR2016.
- Computer vision based mouse66
A computer vision based mouse, which can control and command the cursor of a computer or a computerized system using a camera, which has regions corresponding to buttons for clicking.
- Cross-lingual Visual Pre-training for Multimodal Machine Translation57
This paper extends the translation language modelling with masked region classification and performs pre-training with three-way parallel vision & language corpora to learn visually-grounded cross-lingual representations and shows that when fine-tuned for multimodal machine translation, these models obtain state-of-the-art performance.
- Graph Transduction as a Non-Cooperative Game55
This article proposes a radically different perspective on transduction, based on game-theoretic notions, that is inherently a multiclass approach and imposes no constraint whatsoever on the structure of the pairwise similarity matrix, being able to naturally deal with asymmetric and negative similarities alike.
- CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions52
The results show that even though the questions in CRAFT are easy for humans, the tested baseline models, including existing state-of-the-art methods, do not yet deal with the challenges posed in the benchmark.
- SLAMP: Stochastic Latent Appearance and Motion Prediction50
This work reason about appearance and motion in the video stochastically by predicting the future based on the motion history, and significantly outperforms state-of-the-art models on two challenging real-world autonomous driving datasets with complex motion and dynamic background.
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 2026-10-14. 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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