2.5k citations · 2.8k across the 32 of their papers we have counts for
8 papers · 2 filters
A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models
Quan-Sheng Zeng, Yunheng Li, Qilong Wang +4
Visual token compression is critical for Large Vision-Language Models (LVLMs) to efficiently process high-resolution inputs. Existing methods that typically adopt fixed compression…
Q-Ponder: A Unified Training Pipeline for Reasoning-based Visual Quality Assessment
Zhuoxuan Cai, Jian Zhang, Xinbin Yuan +7
Recent studies demonstrate that multimodal large language models (MLLMs) can proficiently evaluate visual quality through interpretable assessments. However, existing approaches ty…
HyperMotionX: The Dataset and Benchmark with DiT-Based Pose-Guided Human Image Animation of Complex Motions
Shuolin Xu, Siming Zheng, Ziyi Wang +7
Recent advances in diffusion models have significantly improved conditional video generation, particularly in the pose-guided human image animation task. Although existing methods…
MagicTryOn: Harnessing Diffusion Transformer for Garment-Preserving Video Virtual Try-on
Guangyuan Li, Siming Zheng, Hao Zhang +6
Video Virtual Try-On (VVT) aims to synthesize garments that appear natural across consecutive video frames, capturing both their dynamics and interactions with human motion. Despit…
Photography Perspective Composition: Towards Aesthetic Perspective Recommendation
Lujian Yao, Siming Zheng, Xinbin Yuan +5
Traditional photography composition approaches are dominated by 2D cropping-based methods. However, these methods fall short when scenes contain poorly arranged subjects. Professio…
A Temporal Modeling Framework for Video Pre-Training on Video Instance Segmentation
Qing Zhong, Peng-Tao Jiang, Wen Wang +3
Contemporary Video Instance Segmentation (VIS) methods typically adhere to a pre-train then fine-tune regime, where a segmentation model trained on images is fine-tuned on videos.…
M2N2V2: Multi-Modal Unsupervised and Training-free Interactive Segmentation
Markus Karmann, Peng-Tao Jiang, Bo Li +1
We present Markov Map Nearest Neighbor V2 (M2N2V2), a novel and simple, yet effective approach which leverages depth guidance and attention maps for unsupervised and training-free…
DepthMaster: Taming Diffusion Models for Monocular Depth Estimation
Ziyang Song, Zerong Wang, Bo Li +5
Monocular depth estimation within the diffusion-denoising paradigm demonstrates impressive generalization ability but suffers from low inference speed. Recent methods adopt a singl…