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Found 15 papers, 8 papers with code
MAR-3D: Progressive Masked Auto-regressor for High-Resolution 3D Generation
Recent advances in auto-regressive transformers have revolutionized generative modeling across different domains, from language processing to visual generation, demonstrating remarkable capabilities.
MuMA: 3D PBR Texturing via Multi-Channel Multi-View Generation and Agentic Post-Processing
Current methods for 3D generation still fall short in physically based rendering (PBR) texturing, primarily due to limited data and challenges in modeling multi-channel materials.
Text-Animator: Controllable Visual Text Video Generation
Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising.
ID-Animator: Zero-Shot Identity-Preserving Human Video Generation
In this study, we present \textbf{ID-Animator}, a zero-shot human-video generation approach that can perform personalized video generation given a single reference facial image without further training.
Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning
To address these challenges, we collect and introduce the large-scale Visual CoT dataset comprising 438k question-answer pairs, annotated with intermediate bounding boxes highlighting key regions essential for answering the questions.
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
Contrastive Language-Image Pre-training (CLIP) has recently shown great promise in pixel-level zero-shot learning tasks.
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 #11 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
