15 citations · 57 across the 20 of their papers we have counts for
21 papers
SPIDER: Multi-Layer Semantic Token Pruning and Adaptive Sub-Layer Skipping in Multimodal Large Language Models
Tianxiang Chen, Zhentao Tan, Zi Ye +9
Multimodal Large Language Models face significant efficiency challenges that stem from two distinct yet coupled sources: data redundancy and computational redundancy. While most me…
Learning to Focus and Precise Cropping: A Reinforcement Learning Framework with Information Gaps and Grounding Loss for MLLMs
Xuanpu Zhao, Zhentao Tan, Dianmo Sheng +6
To enhance the perception and reasoning capabilities of multimodal large language models in complex visual scenes, recent research has introduced agent-based workflows. In these wo…
Flora: Effortless Context Construction to Arbitrary Length and Scale
Tianxiang Chen, Zhentao Tan, Xiaofan Bo +5
Effectively handling long contexts is challenging for Large Language Models (LLMs) due to the rarity of long texts, high computational demands, and substantial forgetting of short-…
Llama SLayer 8B: Shallow Layers Hold the Key to Knowledge Injection
Tianxiang Chen, Zhentao Tan, Tao Gong +5
As a manner to augment pre-trained large language models (LLM), knowledge injection is critical to develop vertical domain large models and has been widely studied. Although most c…
Mixture-of-Noises Enhanced Forgery-Aware Predictor for Multi-Face Manipulation Detection and Localization
Changtao Miao, Qi Chu, Tao Gong +6
With the advancement of face manipulation technology, forgery images in multi-face scenarios are gradually becoming a more complex and realistic challenge. Despite this, detection…
Transformer based Pluralistic Image Completion with Reduced Information Loss
Qiankun Liu, Yuqi Jiang, Zhentao Tan +5
Transformer based methods have achieved great success in image inpainting recently. However, we find that these solutions regard each pixel as a token, thus suffering from an infor…
MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection
Tianxiang Chen, Zi Ye, Zhentao Tan +6
Recently, infrared small target detection (ISTD) has made significant progress, thanks to the development of basic models. Specifically, the models combining CNNs with transformers…
Bootstrapping Audio-Visual Segmentation by Strengthening Audio Cues
Tianxiang Chen, Zhentao Tan, Tao Gong +6
How to effectively interact audio with vision has garnered considerable interest within the multi-modality research field. Recently, a novel audio-visual segmentation (AVS) task ha…
TCI-Former: Thermal Conduction-Inspired Transformer for Infrared Small Target Detection
Tianxiang Chen, Zhentao Tan, Qi Chu +3
Infrared small target detection (ISTD) is critical to national security and has been extensively applied in military areas. ISTD aims to segment small target pixels from background…
SimAC: A Simple Anti-Customization Method for Protecting Face Privacy against Text-to-Image Synthesis of Diffusion Models
Feifei Wang, Zhentao Tan, Tianyi Wei +2
Despite the success of diffusion-based customization methods on visual content creation, increasing concerns have been raised about such techniques from both privacy and political…
Towards More Unified In-context Visual Understanding
Dianmo Sheng, Dongdong Chen, Zhentao Tan +7
The rapid advancement of large language models (LLMs) has accelerated the emergence of in-context learning (ICL) as a cutting-edge approach in the natural language processing domai…
Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal
Zhentao Tan, Yue Wu, Qiankun Liu +4
Image restoration under adverse weather conditions (e.g., rain, snow and haze) is a fundamental computer vision problem and has important indications for various downstream applica…
HQ-50K: A Large-scale, High-quality Dataset for Image Restoration
Qinhong Yang, Dongdong Chen, Zhentao Tan +6
This paper introduces a new large-scale image restoration dataset, called HQ-50K, which contains 50,000 high-quality images with rich texture details and semantic diversity. We ana…
Multi-spectral Class Center Network for Face Manipulation Detection and Localization
Changtao Miao, Qi Chu, Zhentao Tan +7
As deepfake content proliferates online, advancing face manipulation forensics has become crucial. To combat this emerging threat, previous methods mainly focus on studying how to…
UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection
Wanyi Zhuang, Qi Chu, Zhentao Tan +5
Intra-frame inconsistency has been proved to be effective for the generalization of face forgery detection. However, learning to focus on these inconsistency requires extra pixel-l…
Reduce Information Loss in Transformers for Pluralistic Image Inpainting
Qiankun Liu, Zhentao Tan, Dongdong Chen +6
Transformers have achieved great success in pluralistic image inpainting recently. However, we find existing transformer based solutions regard each pixel as a token, thus suffer f…
HairCLIP: Design Your Hair by Text and Reference Image
Tianyi Wei, Dongdong Chen, Wenbo Zhou +5
Hair editing is an interesting and challenging problem in computer vision and graphics. Many existing methods require well-drawn sketches or masks as conditional inputs for editing…
Diverse Semantic Image Synthesis via Probability Distribution Modeling
Zhentao Tan, Menglei Chai, Dongdong Chen +5
Semantic image synthesis, translating semantic layouts to photo-realistic images, is a one-to-many mapping problem. Though impressive progress has been recently made, diverse seman…
Efficient Semantic Image Synthesis via Class-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +6
Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activatio…
MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing
Zhentao Tan, Menglei Chai, Dongdong Chen +5
Despite the recent success of face image generation with GANs, conditional hair editing remains challenging due to the under-explored complexity of its geometry and appearance. In…
Rethinking Spatially-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +5
Spatially-adaptive normalization is remarkably successful recently in conditional semantic image synthesis, which modulates the normalized activation with spatially-varying transfo…