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Found 10 papers, 3 papers with code
Meta-Auxiliary Learning for Micro-Expression Recognition
Micro-expressions (MEs) are involuntary movements revealing people's hidden feelings, which has attracted numerous interests for its objectivity in emotion detection.
DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point Prediction
Document image dewarping is a crucial task in computer vision with numerous practical applications.
GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning
To tackle these issues, we propose GPT4Motion, a training-free framework that leverages the planning capability of large language models such as GPT, the physical simulation strength of Blender, and the excellent image generation ability of text-to-image diffusion models to enhance the quality of video synthesis.
ImageBind-LLM: Multi-modality Instruction Tuning
During training, we adopt a learnable bind network to align the embedding space between LLaMA and ImageBind's image encoder.
DPL: Decoupled Prompt Learning for Vision-Language Models
Prompt learning has emerged as an efficient and effective approach for transferring foundational Vision-Language Models (e. g., CLIP) to downstream tasks.
Progressive Visual Prompt Learning with Contrastive Feature Re-formation
To the best of our knowledge, we are the first to demonstrate the superior performance of visual prompts in V-L models to previous prompt-based methods in downstream tasks.
Real-Time Image Demoireing on Mobile Devices
In this paper, we launch the first study on accelerating demoireing networks and propose a dynamic demoireing acceleration method (DDA) towards a real-time deployment on mobile devices.
Weakly-supervised Instance Segmentation via Class-agnostic Learning with Salient Images
Humans have a strong class-agnostic object segmentation ability and can outline boundaries of unknown objects precisely, which motivates us to propose a box-supervised class-agnostic object segmentation (BoxCaseg) based solution for weakly-supervised instance segmentation.
Ranked #5 on
Box-supervised Instance Segmentation
on COCO test-dev
(using extra training data)
Hierarchical Reinforcement Learning for Multi-agent MOBA Game
Real Time Strategy (RTS) games require macro strategies as well as micro strategies to obtain satisfactory performance since it has large state space, action space, and hidden information.
