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Found 18 papers, 17 papers with code
NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images.
PixelFlow: Pixel-Space Generative Models with Flow
We present PixelFlow, a family of image generation models that operate directly in the raw pixel space, in contrast to the predominant latent-space models.
Ranked #36 on
Image Generation
on ImageNet 256x256
FlashVideo:Flowing Fidelity to Detail for Efficient High-Resolution Video Generation
DiT diffusion models have achieved great success in text-to-video generation, leveraging their scalability in model capacity and data scale.
Goku: Flow Based Video Generative Foundation Models
This paper introduces Goku, a state-of-the-art family of joint image-and-video generation models leveraging rectified flow Transformers to achieve industry-leading performance.
Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM
Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality of output videos.
IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model
The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities.
Zero-shot Image Editing with Reference Imitation
Image editing serves as a practical yet challenging task considering the diverse demands from users, where one of the hardest parts is to precisely describe how the edited image should look like.
Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
(3) A text-conditional image generation model with 775M parameters, from two-stage training on LAION-COCO and high aesthetics quality images, demonstrating competitive performance of visual quality and text alignment.
Ranked #42 on
Image Generation
on ImageNet 256x256
FlashFace: Human Image Personalization with High-fidelity Identity Preservation
This work presents FlashFace, a practical tool with which users can easily personalize their own photos on the fly by providing one or a few reference face images and a text prompt.
GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest
Before sending to LLM, the reference is replaced by RoI features and interleaved with language embeddings as a sequence.
Ranked #1 on
Visual Question Answering (VQA)
on VCR (Q-AR) test
MultiModal-GPT: A Vision and Language Model for Dialogue with Humans
To further enhance the ability to chat with humans of the MultiModal-GPT, we utilize language-only instruction-following data to train the MultiModal-GPT jointly.
Dense Distinct Query for End-to-End Object Detection
Concretely, we first lay dense queries like traditional detectors and then select distinct ones for one-to-one assignments.
Ranked #4 on
Object Detection
on CrowdHuman (full body)
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO series and is easily extensible for many object recognition tasks such as instance segmentation and rotated object detection.
Ranked #1 on
Object Detection In Aerial Images
on DOTA 1.0
Consistent-Teacher: Towards Reducing Inconsistent Pseudo-targets in Semi-supervised Object Detection
In this study, we dive deep into the inconsistency of pseudo targets in semi-supervised object detection (SSOD).
What Are Expected Queries in End-to-End Object Detection?
As both sparse and dense queries are imperfect, then \emph{what are expected queries in end-to-end object detection}?
Group R-CNN for Weakly Semi-supervised Object Detection with Points
The core of this task is to train a point-to-box regressor on well-labeled images that can be used to predict credible bounding boxes for each point annotation.
Group Fisher Pruning for Practical Network Compression
Our method can be used to prune any structures including those with coupled channels.
Ranked #4 on
Network Pruning
on ImageNet
Scale-Equalizing Pyramid Convolution for Object Detection
Inspired by this, a convolution across the pyramid level is proposed in this study, which is termed pyramid convolution and is a modified 3-D convolution.
Ranked #89 on
Object Detection
on COCO test-dev
