3 citations · 6 across the 11 of their papers we have counts for
12 papers
PhyGround: Benchmarking Physical Reasoning in Generative World Models
Juyi Lin, Arash Akbari, Yumei He +13
Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…
Demystifying When Pruning Works via Representation Hierarchies
Shwai He, Guoheng Sun, Haichao Zhang +2
Network pruning, which removes less important parameters or architectures, is often expected to improve efficiency while preserving performance. However, this expectation does not…
ThinkJEPA: Empowering Latent World Models with Large Vision-Language Reasoning Model
Haichao Zhang, Yijiang Li, Shwai He +5
Recent progress in latent world models (e.g., V-JEPA2) has shown promising capability in forecasting future world states from video observations. Nevertheless, dense prediction fro…
LinkedOut: Linking World Knowledge Representation Out of Video LLM for Next-Generation Video Recommendation
Haichao Zhang, Yao Lu, Lichen Wang +4
Video Large Language Models (VLLMs) unlock world-knowledge-aware video understanding through pretraining on internet-scale data and have already shown promise on tasks such as movi…
Dense Video Understanding with Gated Residual Tokenization
Haichao Zhang, Wenhao Chai, Shwai He +2
High temporal resolution is essential for capturing fine-grained details in video understanding. However, current video large language models (VLLMs) and benchmarks mostly rely on…
Out-of-Sight Embodied Agents: Multimodal Tracking, Sensor Fusion, and Trajectory Forecasting
Haichao Zhang, Yi Xu, Yun Fu
Trajectory prediction is a fundamental problem in computer vision, vision-language-action models, world models, and autonomous systems, with broad impact on autonomous driving, rob…
VQToken: Neural Discrete Token Representation Learning for Extreme Token Reduction in Video Large Language Models
Haichao Zhang, Yun Fu
Token-based video representation has emerged as a promising approach for enabling large language models (LLMs) to interpret video content. However, existing token reduction techniq…
OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising
Haichao Zhang, Yi Xu, Hongsheng Lu +2
Trajectory prediction is fundamental in computer vision and autonomous driving, particularly for understanding pedestrian behavior and enabling proactive decision-making. Existing…
Layout Sequence Prediction From Noisy Mobile Modality
Haichao Zhang, Yi Xu, Hongsheng Lu +2
Trajectory prediction plays a vital role in understanding pedestrian movement for applications such as autonomous driving and robotics. Current trajectory prediction models depend…
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection
Haichao Zhang, Can Qin, Yu Yin +1
Camouflaged objects that blend into natural scenes pose significant challenges for deep-learning models to detect and synthesize. While camouflaged object detection is a crucial ta…
Fine-grained Identity Preserving Landmark Synthesis for Face Reenactment
Haichao Zhang, Youcheng Ben, Weixi Zhang +3
Recent face reenactment works are limited by the coarse reference landmarks, leading to unsatisfactory identity preserving performance due to the distribution gap between the manip…
Sketch Me A Video
Haichao Zhang, Gang Yu, Tao Chen +1
Video creation has been an attractive yet challenging task for artists to explore. With the advancement of deep learning, recent works try to utilize deep convolutional neural netw…