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Found 19 papers, 11 papers with code
Narrative Action Evaluation with Prompt-Guided Multimodal Interaction
NAE is a more challenging task because it requires both narrative flexibility and evaluation rigor.
Attacking Transformers with Feature Diversity Adversarial Perturbation
Understanding the mechanisms behind Vision Transformer (ViT), particularly its vulnerability to adversarial perturba tions, is crucial for addressing challenges in its real-world applications.
FreeMan: Towards Benchmarking 3D Human Pose Estimation under Real-World Conditions
To facilitate the development of 3D pose estimation, we present FreeMan, the first large-scale, multi-view dataset collected under the real-world conditions.
NPF-200: A Multi-Modal Eye Fixation Dataset and Method for Non-Photorealistic Videos
Non-photorealistic videos are in demand with the wave of the metaverse, but lack of sufficient research studies.
Dance with You: The Diversity Controllable Dancer Generation via Diffusion Models
In this paper, we introduce a novel multi-dancer synthesis task called partner dancer generation, which involves synthesizing virtual human dancers capable of performing dance with users.
C2F2NeUS: Cascade Cost Frustum Fusion for High Fidelity and Generalizable Neural Surface Reconstruction
There is an emerging effort to combine the two popular 3D frameworks using Multi-View Stereo (MVS) and Neural Implicit Surfaces (NIS) with a specific focus on the few-shot / sparse view setting.
REC-MV: REconstructing 3D Dynamic Cloth from Monocular Videos
To address the above limitations, in this paper, we formulate this task as an optimization problem of 3D garment feature curves and surface reconstruction from monocular video.
Semantic Human Parsing via Scalable Semantic Transfer over Multiple Label Domains
This paper presents Scalable Semantic Transfer (SST), a novel training paradigm, to explore how to leverage the mutual benefits of the data from different label domains (i. e. various levels of label granularity) to train a powerful human parsing network.
NeMF: Inverse Volume Rendering with Neural Microflake Field
Recovering the physical attributes of an object's appearance from its images captured under an unknown illumination is challenging yet essential for photo-realistic rendering.
Dynamic Feature Pruning and Consolidation for Occluded Person Re-Identification
The framework mainly consists of a sparse encoder, a multi-view feature mathcing module, and a feature consolidation decoder.
Active Domain Adaptation with Multi-level Contrastive Units for Semantic Segmentation
A simple pixel selection strategy followed with the construction of multi-level contrastive units is introduced to optimize the model for both domain adaptation and active supervised learning.
High-resolution Face Swapping via Latent Semantics Disentanglement
Although previous research can leverage generative priors to produce high-resolution results, their quality can suffer from the entangled semantics of the latent space.
A strong baseline for image and video quality assessment
In this work, we present a simple yet effective unified model for perceptual quality assessment of image and video.
Considering user agreement in learning to predict the aesthetic quality
In this paper, we thus propose (1) a re-adapted multi-task attention network to predict both the mean opinion score and the standard deviation in an end-to-end manner; (2) a brand-new confidence interval ranking loss that encourages the model to focus on image-pairs that are less certain about the difference of their aesthetic scores.
Multi-Modal Aesthetic Assessment for MObile Gaming Image
Our inclination is to seek and learn the correlations between different aesthetic relevant dimensions to further boost the generalization performance in predicting all the aesthetic dimensions.
Subjective and Objective Quality Assessment of Mobile Gaming Video
Nowadays, with the vigorous expansion and development of gaming video streaming techniques and services, the expectation of users, especially the mobile phone users, for higher quality of experience is also growing swiftly.
GPM: A Generic Probabilistic Model to Recover Annotator's Behavior and Ground Truth Labeling
In the big data era, data labeling can be obtained through crowdsourcing.
GANs-NQM: A Generative Adversarial Networks based No Reference Quality Assessment Metric for RGB-D Synthesized Views
In this paper, we proposed a no-reference (NR) quality metric for RGB plus image-depth (RGB-D) synthesis images based on Generative Adversarial Networks (GANs), namely GANs-NQM.
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
In this paper we present a hybrid active sampling strategy for pairwise preference aggregation, which aims at recovering the underlying rating of the test candidates from sparse and noisy pairwise labelling.
