Search Results for author:
Found 12 papers, 7 papers with code
ID-Animator: Zero-Shot Identity-Preserving Human Video Generation
Based on this pipeline, a random face reference training method is further devised to precisely capture the ID-relevant embeddings from reference images, thus improving the fidelity and generalization capacity of our model for ID-specific video generation.
Visual CoT: Unleashing Chain-of-Thought Reasoning in Multi-Modal Language Models
This paper presents Visual CoT, a novel pipeline that leverages the reasoning capabilities of multi-modal large language models (MLLMs) by incorporating visual Chain-of-Thought (CoT) reasoning.
Prompt Highlighter: Interactive Control for Multi-Modal LLMs
Without tuning on LLaVA-v1. 5, our method secured 70. 7 in the MMBench test and 1552. 5 in MME-perception.
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
For example, training on the context length of 8192 needs 16x computational costs in self-attention layers as that of 2048.
TagCLIP: Improving Discrimination Ability of Open-Vocabulary Semantic Segmentation
However, existing models easily misidentify input pixels from unseen classes, thus confusing novel classes with semantically-similar ones.
StraIT: Non-autoregressive Generation with Stratified Image Transformer
We propose Stratified Image Transformer(StraIT), a pure non-autoregressive(NAR) generative model that demonstrates superiority in high-quality image synthesis over existing autoregressive(AR) and diffusion models(DMs).
What Makes for Good Tokenizers in Vision Transformer?
The architecture of transformers, which recently witness booming applications in vision tasks, has pivoted against the widespread convolutional paradigm.
On Efficient Transformer-Based Image Pre-training for Low-Level Vision
Pre-training has marked numerous state of the arts in high-level computer vision, while few attempts have ever been made to investigate how pre-training acts in image processing systems.
Ranked #5 on
Image Super-Resolution
on Set5 - 2x upscaling
(using extra training data)
Blending Anti-Aliasing into Vision Transformer
In this work, we analyze the uncharted problem of aliasing in vision transformer and explore to incorporate anti-aliasing properties.
Temporal Interlacing Network
In this way, a heavy temporal model is replaced by a simple interlacing operator.
Make a Face: Towards Arbitrary High Fidelity Face Manipulation
Recent studies have shown remarkable success in face manipulation task with the advance of GANs and VAEs paradigms, but the outputs are sometimes limited to low-resolution and lack of diversity.
Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Translation
Facial landmark detection, or face alignment, is a fundamental task that has been extensively studied.
Ranked #18 on
Face Alignment
on WFLW
