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Found 29 papers, 15 papers with code
DreamOmni: Unified Image Generation and Editing
We begin by analyzing existing frameworks and the requirements of downstream tasks, proposing a unified framework that integrates both T2I models and various editing tasks.
A Survey on Private Transformer Inference
Transformer models have revolutionized AI, enabling applications like content generation and sentiment analysis.
CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation
To Inherit the advantages of MM-DiT, we use a separate set of network weights to process the layout, treating it as equally important as the image and text modalities.
Boosting 3D Object Generation through PBR Materials
By analyzing the components of PBR materials, we choose to consider albedo, roughness, metalness, and bump maps.
UniRec: A Dual Enhancement of Uniformity and Frequency in Sequential Recommendations
UniRec leverages sequence uniformity and item frequency to enhance performance, particularly improving the representation of non-uniform sequences and less-frequent items.
ByteEdit: Boost, Comply and Accelerate Generative Image Editing
Recent advancements in diffusion-based generative image editing have sparked a profound revolution, reshaping the landscape of image outpainting and inpainting tasks.
1st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation
The recent transformer-based models have dominated the Referring Video Object Segmentation (RVOS) task due to the superior performance.
Offloading and Quality Control for AI Generated Content Services in 6G Mobile Edge Computing Networks
In pursuit of enhancing the accessibility of AIGC services, the deployment of AIGC models (e. g., diffusion models) to edge servers and local devices has become a prevailing trend.
Open-Vocabulary Segmentation with Semantic-Assisted Calibration
We attribute this to the in-vocabulary embedding and domain-biased CLIP prediction.
Universal Segmentation at Arbitrary Granularity with Language Instruction
This paper aims to achieve universal segmentation of arbitrary semantic level.
Ranked #1 on
Referring Expression Segmentation
on RefCOCOg-test
(using extra training data)
LLMGA: Multimodal Large Language Model based Generation Assistant
In the first stage, we train the MLLM to grasp the properties of image generation and editing, enabling it to generate detailed prompts.
Automatic Animation of Hair Blowing in Still Portrait Photos
Considering the complexity of hair structure, we innovatively treat hair wisp extraction as an instance segmentation problem, where a hair wisp is referred to as an instance.
DiffI2I: Efficient Diffusion Model for Image-to-Image Translation
Compared to traditional DMs, the compact IPR enables DiffI2I to obtain more accurate outcomes and employ a lighter denoising network and fewer iterations.
SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
To address this issue, we propose Semantic-assisted Object Cluster (SOC), which aggregates video content and textual guidance for unified temporal modeling and cross-modal alignment.
Ranked #2 on
Referring Expression Segmentation
on A2D Sentences
(using extra training data)
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation
Recently, open-vocabulary learning has emerged to accomplish segmentation for arbitrary categories of text-based descriptions, which popularizes the segmentation system to more general-purpose application scenarios.
Ranked #7 on
Open Vocabulary Panoptic Segmentation
on ADE20K
Global Knowledge Calibration for Fast Open-Vocabulary Segmentation
Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred to as open-vocabulary semantic segmentation (OVS).
Knowledge Distillation
Open Vocabulary Semantic Segmentation
+4
DiffIR: Efficient Diffusion Model for Image Restoration
Diffusion model (DM) has achieved SOTA performance by modeling the image synthesis process into a sequential application of a denoising network.
Knowledge Distillation based Degradation Estimation for Blind Super-Resolution
It consists of a knowledge distillation based implicit degradation estimator network (KD-IDE) and an efficient SR network.
Basic Binary Convolution Unit for Binarized Image Restoration Network
In this study, we reconsider components in binary convolution, such as residual connection, BatchNorm, activation function, and structure, for IR tasks.
Mobile Edge Computing, Metaverse, 6G Wireless Communications, Artificial Intelligence, and Blockchain: Survey and Their Convergence
Compared to cloud computing, as the distributed and closer infrastructure, the convergence of MEC with other emerging technologies, including the Metaverse, 6G wireless communications, artificial intelligence (AI), and blockchain, also solves the problems of network resource allocation, more network load as well as latency requirements.
Structured Sparsity Learning for Efficient Video Super-Resolution
In SSL, we design pruning schemes for several key components in VSR models, including residual blocks, recurrent networks, and upsampling networks.
Human De-occlusion: Invisible Perception and Recovery for Humans
Besides, an Amodal Human Perception dataset (AHP) is collected to settle the task of human de-occlusion.
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
Specifically, a new generator architecture is proposed to simultaneously transfer color/texture styles and transform local facial shapes into anime-like counterparts based on the style of a reference anime-face, while preserving the global structure of the source photo-face.
Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
Extensive experiments conducted on the three public domain face aging datasets (MORPH Album 2, CACD-VS and FG-NET) have shown the effectiveness of the proposed approach and the value of the constructed CAF dataset on AIFR.
Ranked #3 on
Age-Invariant Face Recognition
on MORPH Album2
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
Specifically, we find that a large class of primal and primal-dual operator splitting algorithms are all special cases of VMOR-HPE.
CosFace: Large Margin Cosine Loss for Deep Face Recognition
The central task of face recognition, including face verification and identification, involves face feature discrimination.
Ranked #3 on
Face Verification
on YouTube Faces DB
Detecting Faces Using Region-based Fully Convolutional Networks
Face detection has achieved great success using the region-based methods.
Ranked #2 on
Face Detection
on FDDB
Face R-CNN
Faster R-CNN is one of the most representative and successful methods for object detection, and has been becoming increasingly popular in various objection detection applications.
