11 citations · 12 across the 9 of their papers we have counts for
10 papers
One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding
Zheyu Zhang, Ziqi Pang, Shixing Chen +3
Long video understanding is inherently challenging for vision-language models (VLMs) because of the extensive number of frames. With each video frame typically expanding into tens…
MR. Video: "MapReduce" is the Principle for Long Video Understanding
Ziqi Pang, Yu-Xiong Wang
We propose MR. Video, an agentic long video understanding framework that demonstrates the simple yet effective MapReduce principle for processing long videos: (1) Map: independentl…
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception
Ziqi Pang, Xin Xu, Yu-Xiong Wang
With the success of image generation, generative diffusion models are increasingly adopted for discriminative tasks, as pixel generation provides a unified perception interface. Ho…
GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
Lang Lin, Xueyang Yu, Ziqi Pang +1
This paper proposes a novel framework utilizing multi-modal large language models (MLLMs) for referring video object segmentation (RefVOS). Previous MLLM-based methods commonly str…
AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark
Aruna Gauba, Irene Pi, Yunze Man +3
We present AgMMU, a challenging real-world benchmark for evaluating and advancing vision-language models (VLMs) in the knowledge-intensive domain of agriculture. Unlike prior datas…
RandAR: Decoder-only Autoregressive Visual Generation in Random Orders
Ziqi Pang, Tianyuan Zhang, Fujun Luan +5
We introduce RandAR, a decoder-only visual autoregressive (AR) model capable of generating images in arbitrary token orders. Unlike previous decoder-only AR models that rely on a p…
InstructG2I: Synthesizing Images from Multimodal Attributed Graphs
Bowen Jin, Ziqi Pang, Bingjun Guo +3
In this paper, we approach an overlooked yet critical task Graph2Image: generating images from multimodal attributed graphs (MMAGs). This task poses significant challenges due to t…
RMem: Restricted Memory Banks Improve Video Object Segmentation
Junbao Zhou, Ziqi Pang, Yu-Xiong Wang
With recent video object segmentation (VOS) benchmarks evolving to challenging scenarios, we revisit a simple but overlooked strategy: restricting the size of memory banks. This di…
Streaming Motion Forecasting for Autonomous Driving
Ziqi Pang, Deva Ramanan, Mengtian Li +1
Trajectory forecasting is a widely-studied problem for autonomous navigation. However, existing benchmarks evaluate forecasting based on independent snapshots of trajectories, whic…
Frozen Transformers in Language Models Are Effective Visual Encoder Layers
Ziqi Pang, Ziyang Xie, Yunze Man +1
This paper reveals that large language models (LLMs), despite being trained solely on textual data, are surprisingly strong encoders for purely visual tasks in the absence of langu…