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Found 22 papers, 9 papers with code
CrossVTON: Mimicking the Logic Reasoning on Cross-category Virtual Try-on guided by Tri-zone Priors
This framework systematically decomposes the model image into three distinct regions: try-on, reconstruction, and imagination zones.
DynamicControl: Adaptive Condition Selection for Improved Text-to-Image Generation
To enhance the controllability of text-to-image diffusion models, current ControlNet-like models have explored various control signals to dictate image attributes.
Unveil Inversion and Invariance in Flow Transformer for Versatile Image Editing
Leveraging the large generative prior of the flow transformer for tuning-free image editing requires authentic inversion to project the image into the model's domain and a flexible invariance control mechanism to preserve non-target contents.
VIVID-10M: A Dataset and Baseline for Versatile and Interactive Video Local Editing
VIVID-10M is the first large-scale hybrid image-video local editing dataset aimed at reducing data construction and model training costs, which comprises 9. 7M samples that encompass a wide range of video editing tasks.
FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on
Although image-based virtual try-on has made considerable progress, emerging approaches still encounter challenges in producing high-fidelity and robust fitting images across diverse scenarios.
Ranked #1 on
Virtual Try-on
on VITON-HD
Koala-36M: A Large-scale Video Dataset Improving Consistency between Fine-grained Conditions and Video Content
As visual generation technologies continue to advance, the scale of video datasets has expanded rapidly, and the quality of these datasets is critical to the performance of video generation models.
VTON-HandFit: Virtual Try-on for Arbitrary Hand Pose Guided by Hand Priors Embedding
To tackle this issue widely existing in real-world scenarios, we propose VTON-HandFit, leveraging the power of hand priors to reconstruct the appearance and structure for hand occlusion cases.
Oracle Bone Inscriptions Multi-modal Dataset
Oracle bone inscriptions(OBI) is the earliest developed writing system in China, bearing invaluable written exemplifications of early Shang history and paleography.
NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models
Multimodal large language models (MLLMs) contribute a powerful mechanism to understanding visual information building on large language models.
M2-CLIP: A Multimodal, Multi-task Adapting Framework for Video Action Recognition
In this paper, we introduce a novel Multimodal, Multi-task CLIP adapting framework named \name to address these challenges, preserving both high supervised performance and robust transferability.
PortraitBooth: A Versatile Portrait Model for Fast Identity-preserved Personalization
Moreover, these methods often grapple with identity distortion and limited expression diversity.
Probabilistic Triangulation for Uncalibrated Multi-View 3D Human Pose Estimation
The key idea is to use a probability distribution to model the camera pose and iteratively update the distribution from 2D features instead of using camera pose.
Dynamic Frame Interpolation in Wavelet Domain
Video frame interpolation is an important low-level vision task, which can increase frame rate for more fluent visual experience.
Pose-aware Attention Network for Flexible Motion Retargeting by Body Part
Moreover, we also show that our framework can generate reasonable results even for a more challenging retargeting scenario, like retargeting between bipedal and quadrupedal skeletons because of the body part retargeting strategy and PAN.
IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation
Prevailing video frame interpolation algorithms, that generate the intermediate frames from consecutive inputs, typically rely on complex model architectures with heavy parameters or large delay, hindering them from diverse real-time applications.
Ranked #1 on
Video Frame Interpolation
on Middlebury
Learning Comprehensive Motion Representation for Action Recognition
For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame.
Multi-Level Adaptive Region of Interest and Graph Learning for Facial Action Unit Recognition
In order to incorporate the intra-level AU relation and inter-level AU regional relevance simultaneously, a multi-level AU relation graph is constructed and graph convolution is performed to further enhance AU regional features of each level.
STM: SpatioTemporal and Motion Encoding for Action Recognition
Spatiotemporal and motion features are two complementary and crucial information for video action recognition.
Ranked #1 on
Action Recognition In Videos
on HMDB-51
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation
However, since the domain shift between source and target domains, only using the deep features for sample selection is defective.
Ranked #6 on
Partial Domain Adaptation
on Office-31
Parameter Transfer Extreme Learning Machine based on Projective Model
Unlike the existing parameter transfer approaches, which incorporate the source model information into the target by regularizing the di erence between the source and target domain parameters, an intuitively appealing projective-model is proposed to bridge the source and target model parameters.
Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation
Recently, considerable effort has been devoted to deep domain adaptation in computer vision and machine learning communities.
