9 citations · 28 across the 19 of their papers we have counts for
7 papers · 2 filters
Auxiliary Descriptive Knowledge for Few-Shot Adaptation of Vision-Language Model
SuBeen Lee, GilHan Park, WonJun Moon +2
Despite the impressive zero-shot capabilities of Vision-Language Models (VLMs), they often struggle in downstream tasks with distribution shifts from the pre-training data. Few-Sho…
Masking Matters: Unlocking the Spatial Reasoning Capabilities of LLMs for 3D Scene-Language Understanding
Yerim Jeon, Miso Lee, WonJun Moon +1
Recent advances in 3D scene-language understanding have leveraged Large Language Models (LLMs) for 3D reasoning by transferring their general reasoning ability to 3D multi-modal co…
Mitigating Semantic Collapse in Partially Relevant Video Retrieval
WonJun Moon, MinSeok Jung, Gilhan Park +4
Partially Relevant Video Retrieval (PRVR) seeks videos where only part of the content matches a text query. Existing methods treat every annotated text-video pair as a positive and…
Selective Contrastive Learning for Weakly Supervised Affordance Grounding
WonJun Moon, Hyun Seok Seong, Jae-Pil Heo
Facilitating an entity's interaction with objects requires accurately identifying parts that afford specific actions. Weakly supervised affordance grounding (WSAG) seeks to imitate…
Ambiguity-Restrained Text-Video Representation Learning for Partially Relevant Video Retrieval
CH Cho, WJ Moon, W Jun +2
Partially Relevant Video Retrieval~(PRVR) aims to retrieve a video where a specific segment is relevant to a given text query. Typical training processes of PRVR assume a one-to-on…
Prototypes are Balanced Units for Efficient and Effective Partially Relevant Video Retrieval
WonJun Moon, Cheol-Ho Cho, Woojin Jun +5
In a retrieval system, simultaneously achieving search accuracy and efficiency is inherently challenging. This challenge is particularly pronounced in partially relevant video retr…
Temporal Alignment-Free Video Matching for Few-shot Action Recognition
SuBeen Lee, WonJun Moon, Hyun Seok Seong +1
Few-Shot Action Recognition (FSAR) aims to train a model with only a few labeled video instances. A key challenge in FSAR is handling divergent narrative trajectories for precise v…