Search Results for author:
Found 30 papers, 15 papers with code
StableGarment: Garment-Centric Generation via Stable Diffusion
In this paper, we introduce StableGarment, a unified framework to tackle garment-centric(GC) generation tasks, including GC text-to-image, controllable GC text-to-image, stylized GC text-to-image, and robust virtual try-on.
Stable-Makeup: When Real-World Makeup Transfer Meets Diffusion Model
Current makeup transfer methods are limited to simple makeup styles, making them difficult to apply in real-world scenarios.
InstantID: Zero-shot Identity-Preserving Generation in Seconds
There has been significant progress in personalized image synthesis with methods such as Textual Inversion, DreamBooth, and LoRA.
Ranked #2 on
Diffusion Personalization Tuning Free
on AgeDB
ZONE: Zero-Shot Instruction-Guided Local Editing
We then propose a Region-IoU scheme for precise image layer extraction from an off-the-shelf segment model.
SSR-Encoder: Encoding Selective Subject Representation for Subject-Driven Generation
Recent advancements in subject-driven image generation have led to zero-shot generation, yet precise selection and focus on crucial subject representations remain challenging.
IPDreamer: Appearance-Controllable 3D Object Generation with Image Prompts
Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to supervise 3D generation.
Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances
In this era of rapid technical evolution, this review aims to present a comprehensive review of the recent achievements in deep learning based RSOD methods.
Synthesizing Physically Plausible Human Motions in 3D Scenes
Experimental results demonstrate that our framework can synthesize physically plausible long-term human motions in complex 3D scenes.
Controllable Mind Visual Diffusion Model
Brain signal visualization has emerged as an active research area, serving as a critical interface between the human visual system and computer vision models.
PiClick: Picking the desired mask in click-based interactive segmentation
Click-based interactive segmentation aims to generate target masks via human clicking, which facilitates efficient pixel-level annotation and image editing.
MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation
CLIP (Contrastive Language-Image Pretraining) is well-developed for open-vocabulary zero-shot image-level recognition, while its applications in pixel-level tasks are less investigated, where most efforts directly adopt CLIP features without deliberative adaptations.
Towards Open-Vocabulary Video Instance Segmentation
Video Instance Segmentation (VIS) aims at segmenting and categorizing objects in videos from a closed set of training categories, lacking the generalization ability to handle novel categories in real-world videos.
SoftMatch Distance: A Novel Distance for Weakly-Supervised Trend Change Detection in Bi-Temporal Images
Therefore, there is a novel solution that intuitively dividing changes into three trends (``appear'', ``disappear'' and ``transform'') instead of semantic categories, named it trend change detection (TCD) in this paper.
OvarNet: Towards Open-vocabulary Object Attribute Recognition
In this paper, we consider the problem of simultaneously detecting objects and inferring their visual attributes in an image, even for those with no manual annotations provided at the training stage, resembling an open-vocabulary scenario.
Ranked #1 on
Open Vocabulary Attribute Detection
on OVAD benchmark
(using extra training data)
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information
In the exploiting stage, we utilize the extracted NDI to construct a novel negative contrastive learning mechanism and a negative guided instance selection strategy for dealing with the issues of part domination and missing instances, respectively.
Transformers Meet Visual Learning Understanding: A Comprehensive Review
Three image tasks and two video tasks of computer vision are investigated.
Decoupled IoU Regression for Object Detection
Prior works propose to predict Intersection-over-Union (IoU) between bounding boxes and corresponding ground-truths to improve NMS, while accurately predicting IoU is still a challenging problem.
SVIP: Sequence VerIfication for Procedures in Videos
In this paper, we propose a novel sequence verification task that aims to distinguish positive video pairs performing the same action sequence from negative ones with step-level transformations but still conducting the same task.
Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images
To address the above problems, we propose an end-to-end multi-category instance segmentation model, namely Semantic Attention and Scale Complementary Network, which mainly consists of a Semantic Attention (SEA) module and a Scale Complementary Mask Branch (SCMB).
End-to-end Temporal Action Detection with Transformer
Temporal action detection (TAD) aims to determine the semantic label and the temporal interval of every action instance in an untrimmed video.
Ranked #8 on
Temporal Action Localization
on HACS
New Generation Deep Learning For Video Object Dection:A Survery
Video object detection, a basic task in the computer vision field, is rapidly evolving and widely used.
Learning Global Structure Consistency for Robust Object Tracking
Unlike many existing trackers that focus on modeling only the target, in this work, we consider the \emph{transient variations of the whole scene}.
Evolving Metric Learning for Incremental and Decremental Features
Online metric learning has been widely exploited for large-scale data classification due to the low computational cost.
HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces
In this paper, we propose an Online High-quality Anchor Mining Strategy (HAMBox), which explicitly helps outer faces compensate with high-quality anchors.
DuBox: No-Prior Box Objection Detection via Residual Dual Scale Detectors
Working with multi-scale features, the designed dual scale residual unit makes dual scale detectors no longer run independently.
PyramidBox++: High Performance Detector for Finding Tiny Face
With the rapid development of deep convolutional neural network, face detection has made great progress in recent years.
Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images
More recently, a two-stage detector Faster R-CNN is proposed and demonstrated to be a promising tool for object detection in optical remote sensing images, while the sparse and dense characteristic of objects in remote sensing images is complexity.
Polarimetric Convolutional Network for PolSAR Image Classification
Based on sparse scattering coding and convolution neural network, the polarimetric convolutional network is proposed to classify PolSAR images by making full use of polarimetric information.
Face Aging With Identity-Preserved Conditional Generative Adversarial Networks
By grouping faces with target age together, the objective of face aging is equivalent to transferring aging patterns of faces within the target age group to the face whose aged face is to be synthesized.
PyramidBox: A Context-assisted Single Shot Face Detector
This paper proposes a novel context-assisted single shot face detector, named \emph{PyramidBox} to handle the hard face detection problem.
Ranked #4 on
Face Detection
on FDDB
