8 accepted papers
While knowledge distillation has seen widespread use in pre-training and instruction tuning, its application to aligning language models with human preferences remains underexplored, particularly in the more realistic cross-tokenizer setting. The incompatibility of tokenization schemes between teach
In this work, we present a panoramic metric depth foundation model that generalizes across diverse scene distances. We explore a data-in-the-loop paradigm from the view of both data construction and framework design. We collect a large-scale dataset by combining public datasets, high-quality synthet
Signed distance-radiance field (SDF-NeRF) is a promising environment representation that offers both photorealistic rendering and geometric reasoning such as proximity queries for collision avoidance. However, the slow training speed and convergence of SDF-NeRF hinder their use in practical robotic …
Direct Preference Optimization (DPO) is a widely used RL-free method for aligning language models from pairwise preferences, but it models preferences over full sequences even though generation is driven by per-token decisions. Existing token-level extensions typically decompose a sequence-level Bra…
Facial action unit (AU) intensity plays a pivotal role in quantifying fine-grained expression behaviors which is an effective condition for facial expression manipulation. However publicly available datasets containing intensity annotations for multiple AUs remain severely limited often featuring a…
Learning-based gaze estimation methods require large amounts of training data with accurate gaze annotations. Facing such demanding requirements of gaze data collection and annotation, several image synthesis methods were proposed, which successfully redirected gaze directions precisely given the as…
"Real-scale scene flow estimation has become increasingly important for 3D computer vision. Some works successfully estimate real-scale 3D scene flow with LiDAR. However, these ubiquitous and expensive sensors are still unlikely to be equipped widely for real application. Other works use monocular i…
Center of pressure (COP) is an important measurement of postural and gait control in human biomechanical studies. A vision-based estimation of COP metrics offers a way to obtain these gold-standard metrics for the detection of balance and gait problems. In this paper, we propose an end-to-end framew…