Trending Research
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
apple/corenet
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Contrastive learning has emerged as a transformative method for learning effective visual representations through the alignment of image and text embeddings.
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design
Starting with a set of pre-trained LoRA adapters, our gating strategy uses the hidden states to dynamically mix adapted layers, allowing the resulting X-LoRA model to draw upon different capabilities and create never-before-used deep layer-wise combinations to solve tasks.
Improving Diffusion Models for Virtual Try-on
yisol/IDM-VTON
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Finally, we present a customization method using a pair of person-garment images, which significantly improves fidelity and authenticity.
Ranked #1 on
Virtual Try-on
on VITON-HD
AgentScope: A Flexible yet Robust Multi-Agent Platform
With the rapid advancement of Large Language Models (LLMs), significant progress has been made in multi-agent applications.
OpenVoice: Versatile Instant Voice Cloning
The voice styles are not directly copied from and constrained by the style of the reference speaker.
FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent
This paper introduces FlowMap, an end-to-end differentiable method that solves for precise camera poses, camera intrinsics, and per-frame dense depth of a video sequence.
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Compared to both open-source and proprietary models, InternVL 1. 5 shows competitive performance, achieving state-of-the-art results in 8 of 18 benchmarks.
Ranked #6 on
Visual Question Answering
on MM-Vet
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
magic-research/PLLaVA
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arXiv 2024
PLLaVA achieves new state-of-the-art performance on modern benchmark datasets for both video question-answer and captioning tasks.
ConsistentID: Portrait Generation with Multimodal Fine-Grained Identity Preserving
ConsistentID comprises two key components: a multimodal facial prompt generator that combines facial features, corresponding facial descriptions and the overall facial context to enhance precision in facial details, and an ID-preservation network optimized through the facial attention localization strategy, aimed at preserving ID consistency in facial regions.
Make Your LLM Fully Utilize the Context
microsoft/FILM
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While many contemporary large language models (LLMs) can process lengthy input, they still struggle to fully utilize information within the long context, known as the lost-in-the-middle challenge.
